Category Archives: Internet

Personal Analytics with RSS Feeds

I am currently working on a paper on Academic Blogging, from my own experience. And I wanted to do something similar to Stephen Wolfram’s personal analytics of my life. More specifically, I wanted to understand when I do post my blog entries. If I post more entries during office hours, then it should mean that, indeed, I consider my blog as a part of my job (which is something I believe, actually). On the other hand, if I post more in the evening, or in the middle the night, then it could mean that my blog is clearly only for fun, and somehow outside the official academic time schedule.

With the help of @3wen, we have here a function that can read rss feeds, and extract the publication date (and other pieces of information actually),

> library(XML)
> library(dplyr)
> baseRSS <- function(adresse){
+   doc <- try(xmlTreeParse(adresse))
+   if(length(doc)>1){
+   lesArticles <- xpathApply(r <- xmlRoot(doc), "//item") 
+   infosUneEntree <- function(x){
+   title <- sapply(xpathApply(x, "//title"), xmlValue)
+   links <- sapply(xpathApply(x, "//link"), xmlValue)
+   pubDate <- sapply(xpathApply(x, "//pubDate"), xmlValue)
+ return(cbind(title = title, links = links, pubDate = pubDate))
+ }
+ df <- lapply(lesArticles, infosUneEntree)
+ df <- data.frame("rbind", df))
+ return(df)
+ }
+ else{return(NA)}
+ }

The trick is that the page containing the rss feeds is truncated: you get only 30 post (the latest ones). With WordPress, you can easily go further (thanks @3wen) using

> df.freak2 <- baseRSS("")
Namespace prefix dc on creator is not defined
Namespace prefix content on encoded is not defined
Namespace prefix wfw on commentRss is not defined
Namespace prefix slash on comments is not defined
> head(df.freak2)
1       S\303\251ries chronologiques, syllabus
2 Copules et valeurs extr\303\252mes, syllabus
3         Jimmy, Mile End, et le Qu\303\251bec
4                Multivariate Archimax copulas
5                     Somewhere else, part 107
6     Informatique (sans ordinateur), partie 1
                                        links                         pubDate
1 Mon, 06 Jan 2014 00:31:52 +0000
2 Mon, 06 Jan 2014 00:31:21 +0000
3 Sun, 05 Jan 2014 03:33:31 +0000
4 Sat, 04 Jan 2014 11:01:05 +0000
5 Fri, 03 Jan 2014 15:34:29 +0000
6 Fri, 03 Jan 2014 07:15:03 +0000

and if we try to get a page that does not exist, we got the following error

> df.freakFaux <- baseRSS("")
failed to load HTTP resource
Error : 1: failed to load HTTP resource

(unfortunately, I could not do it with for instance). With the following code, we can extract information about all the posts online on my blog

> df.freak <- NULL
> for(i in 1:2000){
+   df.tmp <- baseRSS(paste("", i, sep = ""))
+   if(length(df.tmp)>1){
+     df.freak <- rbind(df.freak, df.tmp)
+   }else{ break }
+ }

All that is just fine. Now, let us write a small function to convert the date into some format I can use (here, I want to study the hour, as well as the week day).

> LD=c("Mon","Tue","Wed","Thu","Fri","Sat","Sun")
> datahour=function(txt){
+ wd=substr(as.character(txt),1,3)
+ wdy=which(LD==wd)
+ y=substr(as.character(txt),13,16)
+ h=substr(as.character(txt),18,19)
+ mn=substr(as.character(txt),21,22)
+ T=as.numeric(h)+as.numeric(mn)/60
+ return(data.frame(weekday=wdy,time=T,year=as.numeric(y)))}

> datarss=function(df){
+ L=unlist(lapply(as.character(df$pubDate),datahour))
+ db=data.frame(
+ D=L[names(L)=="weekday"],
+ T=L[names(L)=="time"],
+ Y=L[names(L)=="year"])
+ return(db)}

Here, I extract the week day, the time in the day (continuous, from 0 till 24, excluded). With the following function we can see the proportion of posts per week day,

> hc=rev(heat.colors(100))
> weekday=function(db,yearinf=FALSE){
+ y=unique(db$Y)
+ if(yearinf==TRUE) y=y[-which.max(y)]
+ if(yearinf==FALSE) y=y[-c(which.max(y),which.min(y))]
+ for(i in y){
+ sB=subset(db,db$Y==i)
+ L=rbind(L,table(sB$D)/nrow(sB)*100)}
+ barplot(t(L[nrow(L):1,]),names=rev(y),col=hc[c(rep(15,5),rep(70,2))])
+ }

(from the bottom to the top, Monday till Friday in light yellow, and Saturday and Sunday in light red). Here, on my own blog, it would be

> weekday(datarss(df.freak))

For the hour, it was slightly more technical (I could not find a decent and simple way to plot the graph I was looking for graph, so I did it by myself)

> hour=function(db,yearinf=FALSE){
+ y=unique(db$Y)
+ if(yearinf==TRUE) y=y[-which.max(y)]
+ if(yearinf==FALSE) y=y[-c(which.max(y),which.min(y))]
+ for(i in y){
+ sB=subset(db,db$Y==i)
+ if(i==2013) t=table(floor((sB$T+6)%%24))/nrow(sB)*100
+ if(i<2013)  t=table(floor(sB$T))/nrow(sB)*100
+ t=t[as.character(0:23)]
+ names(t)=as.character(0:23)
+ t[]=0
+ L=rbind(L,t)}
+ plot(y,rep(24,length(y)),ylim=c(-3,24),axes=FALSE,
+ xlim=c(min(y)-.5,max(y)+.5),xlab="",ylab="",col="white")
+ axis(2)
+ for(i in y){
+ text(i,-2,i)
+ for(j in 0:23){
+ polygon(c(i-.4,i-.4,i+.4,i+.4),
+ c(j,j+1,j+1,j),border=NA,col=hc[L[max(y)-i+1,j+1]/max(L)*98+1])
+ }}}

Just a short comment here. If you look at the code, there is a difference between 2013, and before. The reason is simple: in December 2012, I officially decided to migrate from my old blog to this new one. All the post prior December 2012 were initially published on the old blog. Which was at Montréal (East Coast) time. And I have the feeling that my new blog has a European time. So I did translate, of 6 hours. But the problem might be more complicated actually

> hour(datarss(df.freak))

Now, if we try to comment. On the week days, I find it a bit scary, to see that I spend so much time during the weekends on my (supposed to be) professional blog. And on the hour, I can explain the 2013 easily. I usually spend most of my evenings working (on the blog, or on my courses, or on my research). But usually, I try to avoid posting an entry at 2 a.m. So usually, I keep it until the morning, then when I arrive at the office, I finalize the post, and I make it available.

To understand the difference with previous years, I should probably add a technical comment : the previous blog was on a dotclear platform. On dotclear the Publication time is not exactly the time the post was officially posted online, but the default value is more the time the post was saved for the first time. So there might be some slight differences. I believe that previously, I started to work on a post in the afternoon, then I might spend some time in the evening, even the day after, but when I publish it, if I do not change the default settings, then the publication time would be the afternoon, when I did save the post.

Let us try on another blog… The problem is that is it is quite difficult to get old entries from the rss feeds. Except with WordPress… So I tried to run the previous code on The extraction is simple here.

 501 Tue, 14 May 2013 04:01:

But here again, I do have trouble with 2013. To be more specific, when I look at the feeds I get

while I have on my side

 501 Tue, 14 May 2013 04:01:29 +0000
 502 Mon, 13 May 2013 19:51:06 +0000
 503 Mon, 13 May 2013 04:01:46 +0000
 504 Fri, 10 May 2013 21:11:58 +0000
 505 Fri, 10 May 2013 18:45:48 +0000
 506 Fri, 10 May 2013 17:33:55 +0000
 507 Fri, 10 May 2013 13:00:41 +0000
 508 Fri, 10 May 2013 04:01:53 +0000

I have here a 4 hours difference I cannot explain. But it looks fine before 2013. If I use the previous code, with (in the loop)

+   df.tmp <- baseRSS(paste("", i, sep = ""))

we can get, for instance the following  graph,


We do observe an interesting dynamics here : I guess that previously people were working during the day, and then posting at the end of the day. It looks like, now, people work in the day, sometimes late in the evening, but wait till the next morning to post the entry. Just as I did, in order to read one last time, with a fesh mind… Anyway, I still have to understand what did happened in 2013, just to make sure that the data I extract can be used…

Journalisme Scientifique

Il y a quelques jours, Passeur de Sciences a annoncé que le site du allait abriter plusieurs nouveaux blogs de science. Mon voisin @tomroud a parfaitement résumé la situation en 140 caractères, “plus de blogs sur les sciences sur le…. Mais toujours pas (vraiment) de blogs de scientifiques” (il ajoutait quelques minutes plus tard “il semble donc que l’avenir du blog sur les sciences soit le journalisme scientifique. Pas sûr que ce soit un progrès…“), et @marc_rr a poursuivi la discussion sur son blog – tout se passe comme si – avec un long débat passionnant. N’ayant pas l’habitude de poster des commentaires, je vais plutôt mettre un billet sur mon blog, car je plussoie à la vision de @tomroud !

Je suis en train de finaliser depuis quelques jours un article sur les blogs académiques, et à plusieurs reprises, je me suis interrogé sur la distinction entre l’activité de bloggeur académique, et l’activité de journaliste scientifique. Et le débat des derniers jours (je devrais dire des derniers heures) m’a beaucoup éclairé. Je pourrais faire beaucoup de reproches à @passeursciences (et je l’avais déjà fait une fois, dans Martingale et Journalisme Scientifique, suite à la publication d’un article qui, en quelques lignes, avait balayé le travail de centaines de scientifiques, dont deux chercheurs qui auraient un prix Nobel quelques mois plus tard pour ces travaux, justement). Et beaucoup de compliments (j’adore la chronique “Improbablologie“, même si j’ai pris l’habitude de la lire en la version originale sur, car j’adore l’humour de @marcabrahams). Et dans un commentaire sur le blog de @marc_rr, j’ai eu l’impression que le débat se simplifiait, et que la distinction entre scientifiques et journaliste devenait plus claire,

“Les chercheurs-blogueurs : vous allez sans doute me trouver sévère mais si je dis que j’ai du mal à trouver des chercheurs qui bloguent a/ très régulièrement (au moins une ou deux fois par semaine) b/ en français et sans fautes c/ avec un excellent niveau de vulgarisation (donc sans s’adresser en jargon aux happy few) et d/ sur l’actualité, c’est parce que cela correspond à la réalité. Mais c’est aussi sans doute parce que mes critères sont trop élevés ou trop journalistiques” (a continuer…)

Le problème du jargon scientifique est un vieux problème, qui semble atrocement gêner les journalistes, car ils semblent ne pas le maîtriser. Mais je me suis toujours énervé contre cette tentative de nivellement par le bas (ce qui fait que je prend le clavier aujourd’hui). Cette distanciation forcée enlève beaucoup, et fait rapidement perdre toute crédibilité. Dans son Histoire de la Lecture, Alberto Manguel citait un poète gaulois, Ausone, qui écrivait

Tu as acheté des livres et rempli des rayons, ô amoureux des Muses.
Cela signifie-t-il que tu es désormais savant ?
Si tu achètes aujourd’hui des instruments à cordes, plectre et lyre :
Crois-tu que demain le royaume de la musique t’appartiendra ?

Effectivement, je pense qu’un passionné d’astronomie ne se contente pas de lire Ciel et Espace, il va s’acheter un télescope, et essayer de voir les étoiles par lui même. Et celui qui s’intéresse aux mathématiques ira lire Choux Romanesco etc, avec tout le jargon qui va avec, et voudra aller plus loin. Lorsqu’on a vu les figures d’Esscher, avec les enfants, on a essayé de comprendre pourquoi ça marche ! Alors on a pris nos crayons, nos compas, et on s’est lancé. La science, ça se vit. Je pense que c’est la grande distinction entre les journalistes scientifiques et les bloggers académiques. Dans un vieux billet, sur l’importance du do-it-yourself, j’avais justement expliqué qu’il était important que les gens mettent les mains à la pâte. Je peux citer, par exemple, un autre billet (né d’une discussion avec @imparibus) à l’époque des élections présidentielles. J’avais mis en ligne des graphiques et des codes informatiques pour faire un peu de prévision. Au lieu d’attendre que quelqu’un d’autre le fasse. Dans quelques jours, je dois participer a une discussion (dite grand public) sur le big data. Et un de mes points est qu’il est important de comprendre ce qui se passe, comment fonctionnent les algorithmes qui, soit disant, nous gouvernent. L’affiche de la conférence (j’en reparlerais bientôt sur le blog) associe big data et big brother, et je pense que cette association est (partiellement) fausse : on pense à Big Brother si on se sent dépossédé, et je ne pense pas que ce soit le cas. A condition de comprendre ce qui peut se faire avec du big data, et ce qui reste de l’utopie… Il faut se lancer, et s’approprier le jargon, au contraire ! Je trouve cette démission face à la difficulté incroyable !

Quant à parler de happy-few, c’est tellement méprisant ! Au risque de choquer, il y a du monde qui veut des choses techniques, avec du jargon dedans ! Dans l’article mentionné au début, @passeursciences se félicitait d’avoir 20 millions de pages vues en un peu plus de décembre 2011 (et pas lues comme le dit l’article, malheureusement, on ne saura jamais trop ce que les gens font quand ils arrivent sur nos pages). Je l’en félicite. Personnellement, je suis loin derrière, car depuis décembre 2012 (j’ai fait ma migration assez tardivement) j’en totalise à peine 2 millions. Étant statisticien, je serais le premier à éviter de donner trop de poids à ces chiffres (surtout que je publie, à l’occasion, en anglais, ce qui peut faire augmenter le nombre de lecteurs, et beaucoup de mes articles sont resyndiqués sur des blogs comme , r-bloggers, architects.dzone ou statsblogs – parmi ceux que je connais – ce qui fait baisser le nombre de lecteurs), mais quand on regarde rapidement, ça veut dire que j’ai juste 5 fois moins de pages vues qu’un blog hébergé par le plus grand quotidien français !? En mettant des maths et des formules de codes dans presque tous mes billets ?! J’ai du mal a comprendre l’idée de happy-few, je suis désolé… Cela dit, j’espère que ceux qui viennent sont effectivement happy

PS: sur le français sans faute, je suis malheureusement tout seul sur mon blog, et j’ai beaucoup de mal à me relire moi-même. Mais promis, un jour je me payerais le luxe d’avoir quelqu’un pour relire mes articles avant que je ne les mette en ligne ! Ah ah ah, on peut toujours rêver…


Samedi après-midi, profitant du (relatif) réchauffement, on a marché avec ma fille (la petite, les grands sont au Chili pour la semaine) jusqu’au musée des Beaux-Arts. Traîner au musée une fin d’après-midi doit être une des choses que j’appréciais le plus à l’époque où j’étais étudiant à Paris. Mais Montréal n’est pas Paris (ni New York, comme me le faisait remarquer un collègue, amateur de musées). Pourtant, le musée des Beaux-Arts de Montréal m’avait permis de découvrir Dale Chihuly l’été dernier (une découverte surprenante). Samedi, je pensais qu’on pourrait aller voir Peter Doing, mais je me suis souvenu que les éditions de la Pastèque exposait une quizaine d’artistes, et j’ai eu envie d’aller jeter un œil.

L’idée de l’exposition – ça m’est revenu seulement au beau milieu de la visite – était qu’un artiste devait sélectionner une pièce du musée, et… broder autour.  Une quinzaine d’artistes pour les quinze ans de la maison d’édition. Idée intéressante, non ?

On entre dans l’exposition en découvrant quelques planches de Michel Rabagliati. C’est un peu la star de l’exposition, alors j’ai regardé d’un œil un peu distret car j’espérais surtout découvrir des artistes que je ne connaissais pas. Mais en 5 ou 6 planches, j’avoue qu’une nouvelle fois, Michel m’a époustouflé. On découvre une jolie petite histoire, en espagnol, d’un colleur d’affiche, dont l’affiche mal collée s’envole avec le vent, et reste un morceau… De mémoire, un critique d’art découvre le morceau restant,

et qui s’extasie, criant au génie, même s’il n’a jamais vu le reste de l’affiche…

ce n’est qu’en se retournant qu’on découvre le morceau de l’affiche, qui est resté…la bébé sardine qui fait face à sa maman, comme me l’a expliqué ma fille. Ah, oui,  c’est un tableau de Joan Miró. L’idée est géniale ! Vraiment ! Mais ce qui m’a le plus touché, je pense, c’est la discussion (filmée) de Pascal Girard, et sur sa rencontre avec les ours, inspiré par un dessin de Sarni (Sharni) Pootoogook, un artiste inuit, datant des années 60,

Je ne sais pas si c’est le souvenir de mes vacances californiennes de cet été (où on a effectivement croisé des ours, en se promenant), ou si c’est la réflexion autour du “est-ce que j’ai vraiment vu un ours? est-ce que ça s’est vraiment passé comme je le raconte? est-ce que je me souviens encore de ce que j’ai vu, ou est-ce que l’histoire que j’ai raconté a pris le dessus sur ce que j’ai réellement vécu?” qui m’a troublé… mais je suis resté scotché devant la vidéo et la discussion de Pascal Girard.

Tout son questionnement, je le vis sur mes blogs, où je passe mon temps à essayer de mettre un peu en forme mon quotidien (peut-être un peu trop, à l’occasion) exactement comme Pascal Girard. Toutes proportions gardées, bien entendu, car je ne suis pas un artiste ! Cela dit, lorsque je discutais avec Julien Prévieux (pour préparer la Biennale d’Art Contemporain, à Rennes, en 2010), je m’étais fais la réflexion – à plusieurs reprises – qu’artistes et scientifiques ont beaucoup en commun.

J’avais oublié à quel point une visite rapide de 30 minutes au musée peut susciter comme questionnements. Vivement que j’emmène les grands à leur retour….

Academic Tweets

Almost four years ago, I did tweet, for the very first time of my life:

The goal was to mention a post on my blog (on optimal control). 15,000 tweets later, I wanted to get back on my experience on Twitter, trying to explain why I tweet, and why academics have some kind of legitimacy to be on Twitter (from my understanding of the goal of such a platform) and they should use it by having a Twitter account.

  • How Twitter works?

I guess I should explain what Twitter is, in case some readers do not know it. “Trying to explain Twitter to the non-user has become something like the tech world’s Arthurian challenge, a seemingly impossible task that no-one is able to fully complete” as explained in Theorizing Twitter: Narratives and Identity. But let me try. Rules on Twitter are simple,

  1. you need to create an account, on You have 160 characters for a short bio, and you can use an avatar
  2. then you can starting tweeting, i.e. posting online messages with 140 characters
  3. you can also be passive, and simply follow some discussions… you can type something in the search window, and then you will see all the tweets containing that word (or that sentence), like why do people tweetIt is also possible to follow some hastags (following the symbol) such as , or some people (following the @ symbol) such as @freakonometrics (that’s me).
  4. if you like my tweets (posted under the name @freakonometrics), you can follow me, and I will appear in your so-called TL (or timeline). You will become my follower (of course, if I find your tweets interesting, I might follow you back).
  5. you can also include a picture (one, only). Since a link will be mentioned in your tweet (automatically generated by Twitter), you will have less than 140 characters to tweet.
  6. you can add html links, that will be shortern by Twitter.
  7. if you include a link on a video (say on or a song (say on, then, the object will appear directly in the tweet: followers will see the movie, not only the tweet with a link, see e.g.

Then, there are (almost official) codes

  1. you can retweet a tweet, which means forwarding another user’s tweet to all of your followers. RTs are not endorsement (neither are tweets actually)… You can use the retweet button, or use the old fashion RT (for re-tweet) or MT (for modified tweet) if you had to shorten a tweet. This is important to mention how you get some information in case you want to share it with you followers (it is called a mention, and it is like using a reference in a research paper). Another way of acknowledging the account who originally shared the content being tweeted is to HT the account (hat tip)
  2. you can reply to a tweet using the reply button. If you reply to one of my tweets, your tweet will start with @freakonometrics and only your followers also following me will see it in their tweet list. If you want to share the answer with everyone, the tweet should start with a dot, .@freakonometrics. It is also possible to send direct (private) messages… It is also possible to poke another account if you want to make sure that someone reads your tweet.
  3. it is possible to favorite a tweet, by clicking the yellow star next to the message. If a lot of the people I follow favorite a tweet, it will be more likely to appear in the discover window, even if I do not follow that account. It might also be interesting to favorite tweets since they can appear in some widgets you have on your blog. Keep in mind that some tweets are promoted, meaning that some company pay to have more exposure… promote and favorite are quite different…
  4. there are some strange customs, such as the #FF for follow Friday. On Friday, you can share usernames of your favorite twitterers, the accounts you find interesting. I am not a social person, so I do not use that, and I do not know how to react when someone #FF me (usually I simply favorite, which is a simple way to say thank you without tweeting a stupid “thanks“)
  5. because of the 140 character constraint, a lot of strange words can be used on Twitter, such as “OH” which most often means “overheard“… just go on google to find more…

and there are more unofficial codes (here, it will be rather subjective, so comments are opened if you want to criticize)

  1. when someone RT, MT or HT one of your tweets, it is common to favorite the tweet. Maybe common is not appropriate here : it is something people with a lot of followers did to me a few years ago, which helped me, somehow, to get more popular, and I also try to do it.
  2. do not steal tweets: you should always mention the account that originally shared the content. From an ethical point of view, that’s an obvious statement. But from a technical point of view, with the 140 character rule, it can be complex. I mean, if you want to add “HT @freakonometrics” you have only 120 characters left, so either you shorten the tweet, or you keep the tweet as it was and you tweet right after something like “previous tweet, HT @freakonometrics
  3. it is possible to delete a Tweet. I do not know if there are rules here, because I’ve seen a lot of tweets with invalid urls, or big typos… I do delete some tweets. My rules are : (1) if I see a typo (or a problem with the url), I have the right to correct it, so I can write a new tweet, an delete the previous one; (2) if  a tweet arouses controversy (and if it was not the goal, say that with 140 characters, I got misunderstood), then I delete the tweet: I am not on Twitter to argue, only to share some contents (we’ll get back on that point later on).

See, or An Introduction to Social Media for Scientists, for some advice on how to start  tweeting. So now that we’ve seen how Twitter works, how can we use it? As academics.

  • Are Academics on Twitter ?

Only « one in forty scholars are active on Twitter » as estimated in Priem et al. in 2011. And let’s face it honestly : academics are mainly skeptical about Twitter. For most of them, it’s for their kids, or perhaps for graduate students (if they have some ideas about what Twitter is). But not researchers. I follow (and am followed) by a lot of graduate students, PhD’s or postdocs, and a few more senior researchers. Most of those senior, prominent scientists, share extremely interesting information! I do not discuss the quality here, simply the fact that, indeed, not everyone is willing to go on Twitter. And be active.

But if not everyone is on Twitter, important people are. At least, in Economics. In January, I wanted to go to the conference of the American Economic Association, in Philadelphia, but I could not do it. That’s where the job market for PhD students in Economics took place. But it was extremely active on Twitter (you got updates following frequently the #ASSA2014 hashtag). From my perspective (maybe also the people I follow), it looked like everyone there was on Twitter during that (major) event.

  • Twitter as a Bookmark

I do spend a lot of time online, reading articles, for work, for fun, and sometimes, I’d like to keep tracks of those articles, or posts on blogs, or articles on, etc. The first motivation to use Twitter is because I need bookmarks. With Twitter, those bookmarks are public. It does not mean that I endorse what I read, it should be understood as « I found that interesting, and I want to bookmark it, to find it, someday ». A few years ago, it was difficult to get back old tweets, like those I posted in 2010 or 2011, so I decided to start my Somewhere Else chronicle on this blog: I simply post all the tweets I wrote, to mention readings worth reading, outside my blog, somewhere else. Like that one:

It is clearly not perfect. I got a lot of tweets with questions following that tweet (but I did not answer them, I shared the graph, I did not create it). The point was « that seems to be interesting, and I’d be glad to find it if someday I want to spend more time on linguistic issues ».

As most academics, I do read a lot. And one of our duties is to share information… This was mentioned in Priem and Costello (2010), « the professional impact of Twitter may be particularly pronounced for scholars given that sharing information is a central component of their work » (see also Letierce et al (2010)). They estimated that 30% tweets sent by academics contains a hyperlink to a peer-reviewed resource (usually a pdf file of a research paper). And it is not necessarily a paper published online 24 hours ago : it can also be a paper rediscovered accidentally, or a technical report written a few decades ago that has just been scanned. @coulmont went back on a « strange experience » (as he defined it) a few months ago, when I (re)discovered a post published on his blog almost one year before, tweeted it, and then a buzz started on that old post. At least, that’s what he told me, we’ll never know for sure if this was because of me, or not (I doubt it actually, there were a lot of good reasons to rediscover that post).

Traditionally, academic visibility is measured using citations, meaning that some work has been accepted by (so called) peers, in the scientific community. Academics need to write to have an impact. But a lot of time is spent on reading. This reading activity is missed by standard citation counts (unless you publish a review, for instance).  On Twitter, you can comment, even (briefly) discuss a publication, some tricks on computer codes, share graphical visualization, etc. It is not like posting an anonymous comment on some scientific blog (actually, several blogs do not have open comments any more). On Twitter, there is some kind of credibility, and not only from the academic resume : people know you and follow you. According to Scott Wagers, « good content is propagated rapidly, bad content is not ». Of course, it is not that simple. There is a time for tweeting, clearly. If you tweet when someone with a lot of followers, then things might grow exponentially fast, and within a few hours, a tweet can be RTd a dozen, a hundred, a thousand times (we’ll get back on the viral effect of Twitter at the end of this post).

  • Live-Tweet in Conferences

Another popular use among academics is to use Twitter for live-tweets, see e.g. How People are using Twitter during conference or the interesting “who is going to read 12,000 tweets?!“. But as mentioned on a lot of blogs, one should be careful about live-tweeting. As recalled in Live-tweeting at academic conferences, « with great power comes great responsibility ». Live tweeting is supposed to be fun, but stay polite, and respectful. And use quotation marks. Getting back on the so-called Twittergate (see An Idea is a Dangerous Thing to Quarantine #twittergate), Aaron Bady, used that interesting image, about Twitter within the academic community « I conjured up the image of an appropriate cantankerous old professor yelling at a bunch of punk tweeters to get off his lawn, like Clint Eastwood in Gran Twittarino ».

Now, to be honest, I have been involved in some live-tweet only once, while I was giving a talk, at the World Social Science Forum, a few months ago

But I usually do not live-tweet, I do not feel comfortable with it (I prefer to take notes in my book, even if I might also write a post on my blog later on, but I always ask the speaker if I can quote what he or she said). « Some worried that having someone tweet their insights before they publish might increase the likelihood that they will be scooped by a colleague — although others regarded that notion as slightly paranoid » as mentioned in the Academic Twitterazzi. « The debate over live tweeting at conferences is, in many ways, about control and access: who controls conference space, presentation content, or access to knowledge? » wrote Roopika Risam in Conference Live Tweets: Twitter Good or #Twittergate?.

Beyond those pseudo-ethical considerations, there is also a more practical reason: in mathematics, it is quite difficult to live-tweet. I mean, it is difficult to write equations in Twitter, and a graph without the formal model is usually useless. There might some interest when there are computation issues, to share a visualization for instance (there were interesting experiences in R conferences this summer, e.g. in Lyon).

  • Twitter to Meet People

It is also possible to start discussions on Twitter. But again, I am not a social guy, so I usually do not like that. I mean, if I share a link to an article, it is because I found it interesting. If someone wants me to go further, or to discuss it, why not…. but Twitter is not the place. I prefer my blog, where I do not have the 140 character constraint.

An important issue in Twitter is to speed up connections between scientists. There is nothing new here. Traditionally, scientists have always interacted with other scientists, in sort of one-to-one interactions, attending seminars, conferences, discussion with colleagues. Using the words of Priem et al (2013), « informal conversations have moved out of the faculty lounge to online social media platforms », such as Twitter. One of the interests is to join somehow a larger « virtual department » with colleagues that are not next door, but who might be far away and in other areas of research. One can even discuss with real people, outside academia. Since I have interests in risk modeling, finance, climate, computer science, mathematics, I can also discuss with people working on stock markets, in insurance companies, in data visualization startups, even journalists. The awesome point is that it becomes possible to interact with open minded researchers. As mentioned in Fox (2012) – slightly changing the title – « blogging [and micro blogging] changed how economics share ideas ».

The first step in the scientific process is to find ideas, new ideas or concepts to investigate, datasets to describe. Following interesting people on Twitter can be the first step. The final step is to communicate findings and to disseminate. The time when researchers were studying the table of contents of journals to find interesting articles is behind us. When disseminating on a blog, we can share codes, graphs, datasets, links to additional material. On Twitter, we have to deal with the 140 character constraint, which makes it hard. One idea can be to use a nice visualization, a graph, a map.

  • Personal versus Institutional Accounts

On Twitter, I mainly follow researchers, only a few institutional accounts. For instance, I like the @HarvardBiz to get updates about their blog, and recent articles. It’s like using RSS feed (except that I am not a big fan of RSS). I might also confess that I have been asked, a long time ago, to be the Twitter Manager of the @StatFr account, of the French Statistical Society. But I quickly faced two problems: it is very difficult to be active on two accounts at the same time, especially when they share the same goal (here, it was just tweeting links to interesting articles, related to statistics – as well as activities of the association). And it is difficult to get a clear guideline. I mean, on my Twitter account, I tweet whatever I like. After a few days experiencing the @StatFr account, I had to argue with the President of the Society because of a link I mentioned in one of my tweet, that was too controversial (but, from my point of view, was mentioning interesting statistical issues). So I have to confess I prefer to follow people, more than institutions or groups.

On the other hand, in all you can tweet, academics behind the nature chemistry Twitter account (@NatureChemistry) went back on 4 years of experience. Among lessons learnt, collectively, it was mentioned that with the 140 characters constraint, « clarity is a virtue », which is indeed of the the things you learn with Twitter. Furthermore, they mention that following important researchers in your scientific community on Twitter is interesting. Not only you can discover interesting information. With personal ccounts, you can also learn more personal information. For instance, it’s always a pleasure to get news and updates from Emiliano,


  • The Impact of Twitter in Standard Process of Academic Dissemination

For academics still skeptical about the use of Twitter, I should probably mention Shuai et al. (2012) which proved (following 4,600 papers) that papers mentioned on Twitter are more downloaded, and more cited (see also Eysenbach1 (2011)). Dissemination using Twitter can help to reach other researchers, in your area, but also journalists, people working in the industry or for governmental organization, even members of parliament… It is hard to follow the sequence, but here how it looks like

publication of an academic paper
(in a journal, or on arxiv)

tweet mentioning the paper

mention in a popular blog

mention in a newspaper


Things can go viral easily with Twitter (again, we’ll get back on this point more specifically soon). But still. It is difficult to clearly understand what  happened (in the newspaper, the researchers are usually mentioned, as well as the blog sharing the information, but that’s all…)

  • Having Fun on Twitter

A few weeks ago, I saw a nice graph, on a blog

and I wanted to reproduce it. With a code as simply as possible. Sure, it’s a geek’s thing to try to write codes as short as possible. But that’s fun, really


It was not worst writing a post on my blog, and with a couple of tweets, I keep tracks of that interesting mathematical problem.

People on Twitter try also – sometimes – to have fun, following some hastags, such as, a few weeks ago, e.g.

(see also here for a collection of great tweets) or more recently #SixWordPeerReview,

  • Gaining Time to Discover Interesting Information

So, clearly, you can save time to discover interesting publications, simply by following interesting people. But, as you may imagine, the difficult point is to follow your TL. If you follow, say 400 people, each of them did tweet, on average 5 times in a given day (including RTs), that makes 2000 tweet to read, if you go on Twitter once a day. Much more if you go on Twitter once a week. To save some time, somehow, it is possible to use dedicated websites such as Based on your TL and people you follow, it is possible get a subset of popular tweets and links shared those people you follow. I believe that a similar algorithm is used in the page (probably more based on tweets favored than RTd).

  • My Own Experience on Twitter

Now, to share a bit of my personal experience, I should probably mention that I do not have a cell phone, neither a tablet. So when I go on Twitter, it has to be on my laptop. It might be while cooking and preparing the lunch box for the kids, in the morning, just to get quickly the news from the night. It might also be in the office, when some code is running, and I have to wait. Most of the night it’s in the evening. Once the kids are asleep.

If I look at my tweets, you can see that I RT a lot of tweets (the old way), and a few Twitter accounts (even if I have the feeling that only tweets published more than two years ago appear here)

  • Going viral on Twitter

To conclude, I should warn everyone that Twitter is addictive. And it can be exhilarating and dangerous when things start going viral… For instance, a few days ago, I did post a simple map (without proper references, it was mentioned in another tweet since there were two references, one for each map), and then, in 24 hours, there were almost 1,000 RTs (not to mentioned tweets mentioning that tweets that were also RTd),

The interesting side is that it was a nice opportunity to understand how this viral process works, and @3wen published an interesting post on that experience.

  • Possible Conclusion (?)

Being on Twitter is an amazing experience. I met (at least virtually) a lot of people, that I would have never been interacting with if they were not on Twitter. David Monniaux, editor of the great blog used to be on Twitter (@monniaux), but – according to the legend I read on Twitter – being on Twitter was time consuming (David used to interact a lot), so he decided to quit. Thus, I am glad that I do have neither a smartphone, nor a tablet! Because I would spend hours on Twitter! With moderation, Twitter is a great tool. But to be honest, it’s a little bit crowded… it is a place to be, but it’s hard to have a discussion with other people, with the 140 characters. I really believe it’s not the place to ask questions, and start a discussion. This is why I also try to go on other microblogging plateforms to interact, more confidential… But I won’t mention them here, I’d like to keep it that way.

  • To Go Further

Twitter for academic and engagement
Using Twitter for Curated Academic Content
Beyond citations: scholars’ visibility on the social Web
Live-tweeting at academic conferences
An Introduction to Social Media for Scientists
How People are using Twitter during conference
Using Twitter During an Academic Conference
Presenting for Twitter at Conferences
An Idea is a Dangerous Thing to Quarantine #twittergate
My Norm is More Normal Than Yours: Academic Tweeting and Loose Fish
“But who is going to read 12,000 tweets?!” How researchers can collect and share relevant social media content at conferences
Don’t Have Time to Tweet-bollocks! Twitter can even save you time as a scientist.
The role of Twitter in the life cycle of a scientific publication, and the associated infographics
Can tweets predict citations? (metrics of social impact based on Twitter and correlation with traditional metrics of scientific impact)
All you can tweet
Twitter as tool for strengthen a scientific community
How and why scholars cite on Twitter
Prevalence and use of Twitter among scholars (on
Twitter as a tool for conservation education and outreach: what scientific conferences can do to promote live tweeting
Understanding how Twitter is used to spread scientific messages

Wasting Time (and Givin’ Up)

There was an interesting post, published a few days ago, entitled This Blog is a Waste of My Time. The funny thing is that I had exactly the same experience at the same time. Since 2013 ended, I wanted to update my resume. And I observed that I got zero publications in the past two years years. ZeroNada. Nothing published in 2012 and nothing published in 2013. Of course, it is mainly a timing issue, since several papers are still in the loop, and I might end up with a few papers published in 2014 (at least one was accepted the first week of 2014). But still… When I decided to turn off my laptop yesterday evening at 2 a.m. (this morning actually) I started wondering also if blogging wasn’t a waste of time. Or if it was something else.

  • My Research is a Waste of My Time (and not only mine)

This will sound like a cliché, but academic do waste a lot of time when doing (or pretending doing) some research,

  1. wasting time applying for grants: do I have to be more specific here? By wasting time I mean working during a month (almost) to fill forms, and there then get a “your proposal is extremely interesting, you got positive feedback from the reviewers, unfortunately, there’s no funding from the government…“. We all had this experience. We’re wasting our time here… and the reviewers time, too.
  2. wasting time in committees: as mentioned above, I have to spend time in research committees, reading applications for grants, but also in faculty committed, discussing office allocation for instance. We got more postdocs, visitors, interns than available seats… and for some reasons, I am on the bargaining comity, trying to argue with my colleague that my postdoc staying for 6 weeks should be before his visitor staying for 2 weeks on the priority list. I do have to do this, but you have to admit that, somehow, you waste the time of four tenured professor (plus me, I am not tenured) on some bullshit here… I am also on the PhD comity, where we receive applications. In December, we did spend a lot of time on the application of one candidate, potentially interesting (like many hours, discussing and arguing), and we’re not even sure that if we agree to enroll him in the PhD program, the candidate will join. If he’s not coming, that will be a waste of time
  3. wasting time in the review process: it looks like I spent more time reading and writing reports on others papers than writing my own ! Ok, that might be an actual quote I got from one of my referees in a recent paper… I keep saying that I should start saying “no, I am too busy” when an editor ask me for a review. But I also keep saying that a lot of bullshit managed to get published. So I cannot stand aside and wait. I mean, I could: I’m French and we’re usually good for this kind of things. But I’d rather be involved in the process, advise the editor if the paper is not worth it, and help to improve the paper if it might be interesting. But again, I spend a lot of time in this process. I know what others are doing, but I keep delaying my own. You cannot find my name if you look for articles published in 2012 or 2013, but I am somewhere, as one of those anonymous referees thanked at the end of the article (who sometimes spent more time on the paper than the PhD supervisor who barely knows what the paper is about, but still has his – or her – name on it). There was an interesting post by Rob Hyndman entitled How to get your paper rejected quickly a few weeks ago. I still don’t know if I agree with everything, but I agree that “review­ers spend a great deal of time pro­vid­ing com­ments, and it is dis­re­spect­ful to ignore them” (I would say “might spend“, but I do not want to argue on that point today). A lot of time is wasted in the publication process.
  4. wasting time trying to get data: before Julie started her internship in September, I tried to get datasets to work on demographic problems. I started discussing (and filling) forms to get French datasets, and managed to get a smaller in Québec. The agenda was simple: we work on the small dataset, write the code, and then, once we’ll get the big dataset, we’ll just use the code that we tested on the small one. After 6 months, I still wonder if my form has been accepted, and if, someday, I will be able to get access to this dataset. I know that the dataset exists. I mean, I know that two datasets exist, and I just ask for a merge… but it looks like there might be ethical considerations, so it takes time.

I do waste a lot of time in the process of making research, and I do not mention here procrastination. Actually, I believe that procrastination is extremely important, and is not a waste of time… But I will get back, someday, on that point in another post.

  • My Teaching Related Duties are a Waste of My Time

I will not claim that teaching is a waste of time. I am still extremely pretentious, and I believe that by the end of my courses, my students could actually learn something… But the problem is more on associated duties. One might think of writing the exams (and sketches of solutions) or grading (since I do not have T.A.s to help). It takes time. A lot of time actually. But I won’t consider it as wasted. Two shorts stories to explain what I mean (that occurred in the Autumn session)

  1. in September, I gave a course, and there were 4 tests scheduled. A few hours before the first one, I got an email from a student, asking me to reschedule it because he could not be there. He asked me to postpone his examen a few days after. I said no, essentially because we signed an agreement on the first day, and the student knew by that time that he will not be able to be there for the exam. And never told me before. I decided to stand on this principle. The thing is the student invoked religious matters, and I understood it will start to be stinky soon. But I had principles. I got some moral support from my colleagues, and from my Dean, but everyone was telling me that I was in charge in this battle (“we support you, but you’re on your own“) since we have our academic independence. I did ask for legal backup from the Professors Union (three times) and no feedback. Then, I heard that a letter had been sent to the rector by a lawyer, and within 10 minutes, I gave the student everything he asked. If he asked me to take the test on a Sunday, I would have said yes… Just because lawyers basic rule is to waste others time, or money. So I gave up. I did not want to waste my time on that battle, on my own. The funny (?) side of this story is that so did the student: I agreed to postpone the test at the end of the session, he came for the second test (but never show up in my class) and got a little bit more than 30%. I did not get further news from him, and he did not take the other tests. But I did waste quite some time, and some bad nights and insomnia, too.
  2. in December, I was grading some homework I gave to my students (practical, on databases) and I saw on two forums that a pair of students was asking for help. Actually, it was not help but could you please do this for me ? They did mention the number of their database (each group had a different database, and the person who posted the question in those forums was located in Montréal). This was fraud, or at least fraud attempt. So I gave them 0% – on that specific homework. Students confessed that they did ask for help on the forum (but never asked me anything)… and I gave up. I mean, I decided to grade their work, and I did fill a form for fraud, sent to the faculty, so that it will be someone else’s problem. I did not want to spend time arguing that those students clearly should not get the exam (one of them had only 20% at the final written exam – the other one 36%) : if they want to learn something, taking the course in the Winter session was clearly an opportunity to learn something… But they din’t get it, and I gave up.

I clearly waste time on a lot of things. But when I look back at the past four or five years, I might feel ashamed not to have more prestigious (somehow) publications, lectures notes without typos everywhere, but at least, the blog is something I am still proud of, sort of. And when I end up working, tired, around 2 a.m., I have the feeling that something is wrong, and that a lot of time has been wasted. And I have to confess that I think I should give up on something… But I don’t think it will be on my blogging activity.

Research, and honesty

Some great thoughts about research… via Twitter

Wait… that one was actually a true story

Panel on academic blogging

This Monday, I joint a panel discussion in Montréal on “Minor forms of academic communication: revamping the relationship between science and society?“, at the World Social Science Forum. The Forum was organized by the ISSC, i.e. the UNESCO. Yes, Monday was Thanksgiving in Canada. I have to admit that I was not used to celebrate Thanksgiving, in Europe, but since I have in North America, I try to enjoy it. As you can learn on, at Thanksgiving, you’re supposed to be “Spending Time with Family“. I find it odd that the UNESCO organizes a three day conference on that week-end (the conference started on Sunday actually). It looks like you’re not supposed to have a family life when you’re an academic….

Anyway, that was interesting to join that panel, since I had the opportunity to have interesting discussions with the other members of the panel. I was glad to meet Loïc Le Pape, the editor of a great blog on religion and politics, It was interesting to see that, even if we do blog on very different topics, with very different styles, we both – as academic bloggers – share the same feelings, the same joy and the same fear about blogging. I also enjoyed meeting – finally – the legendary André Gunthert (see You probably know André from his blog The text of his talk on now online there, and I did really appreciate it (anyone interested by academic blogging should probably read it). I was also glad to discuss about Boulet‘s incredible post on his blog entitled “notre Toyota était fantastique“ (we both love Boulet’s work, and more generally graphical novels, what we call bande dessinée in French, the nineth art actually). Boulet is a comic book writer, publishing on a blog for years, and I have to admit that I prefer reading the published books than the blog (his Notes are the paper version of the blog). But last week, I saw something on his blog that I will never be able to read in a book

It is still a cartoon, probably more an autobiographical graphic novel, but those animations are great. For the first time, I really see the interest of blogging in graphical novels. Please, have a look at “notre Toyota était fantastique“, it is really something you should experience… And I was glad to share André’s point of view, since this is exactly his expertise (as a researcher). I hope that we’ll find some time to discuss more about data visualization, since I believe I have a lot to learn from him.

It was also great to finally meet Marin Dacos, one of the founder of, which is the platform hosting now my blog. Hearing some macro-vision about academic blogging was interesting, and complementary compared with blogger’s experiences I’ve been reading those past days to prepare my talk. I was also glad to discuss legal aspects related to blogging, since one of the interest of being hosted by an academic platform is to have some kind of backup and support. One of the issue I should still work on is about adding mentions when I use a picture on my blog. I am aware that it is not fair to avoid citations related to pictures, when I upload them on my blog. A few months back, I decided to add mentions, explaining where each pictures were borrowed from. Then, since the owner of the rights of some pictures was checking on the internet using robots (or simply Google), within a week, I got an email asking me to remove those pictures, since it was illegal. The email was not friendly at all. So I did remove the pictures, and all the citations and mentions. So, if some authors of pictures want me to remove a picture from my blog, or want me to add a mention below, I’d be glad to do so ! Please, just send me an email.

And finally, another interesting experience related to this panel was that, for the first time, I discovered what live tweeting was. So far, it was only a legend, that I could read from here and there (see e.g.…). I had already experience the one tweet to mention a talk, like

but here, I guess for the first time, I experienced live teet,

I found that awesome ! I mean, at first, I find that odd to see me mentioned so many time on consecutive posts on twitter. But it is great to see what people in the room got from my talk (I have to admit that it was not live for me since I do not have a smartphone – not even a phone actually – I did discovered that later, in the evening, when I got back home, after some beers with André and Loïc). I did really enjoy what Ewen did on his blog a few month ago, with a detailed summary of the R conference he went to (see Here, it is the tweet version. And I found it great… I don’t know why it is the first time I see this (I don’t know if it is something you see more in social science than in mathematics, or just due to the fact that I did not attend much conference since I have three kids), but I loved that… Thanks again Ravi.

The role of blogging in academia

In a few days, I will participate to a panel discussion in Montréal, chaired by Marin Dacos, entitled  “Minor forms of academic communication: revamping the relationship between science and society?“, at the World Social Science Forum. I do not have much expertise  (compared with colleagues involved in the panel) even if I frequently observe the community of academic bloggers, and I regularly interact with some of them. For this panel discussion, Marin asked me to share my experience, as an academic blogger. So, let’s try to describe the Freakonometrics adventure…

  1. The origins: why and how the blog started?
  2. The practice: how do I blog?
  3. The future: why is it still worth blogging, in academia?

I will try to organize my post according to these three items (note that you can get directly to each of them if you want to skip some parts). But to be honest, my post will probably get soon very messy…

  • How blogging started – from experience at Univerisité de Rennes to ‘Freakonometrics’

The first version of the blog started at Université de Rennes 1, following a request from the IT department. In 2007 (as far as I remember), someone came up with the idea that all researchers should have a web page, or at least a page explaining their area of expertise, with links to papers, and lecture notes. But a lot of researchers were reluctant, and that IT person thought that blogs might be an interesting alternative. I was (extremely) skeptical, but since I just arrived in Rennes by that time, I thought it could be fun. I did have web pages for my courses (see a relic of the past, for a course on time series I gave 10 years ago, in Paris), and I did have a webpage with weekly updates, that could be called a blog. So I did have some kind of experience. But still.

From a technical point of view, blog is a contracted form of weblog, which is a website made up of ongoing entries, that we will call posts. And those posts are published in reverse chronological order. So it makes it difficult to follows for students, unless they go on the blog frequently. There might be tags and categories, that can be used to distinguish posts related to conference, publications, and teaching. This first blog was a great experience. Teaching was fun, students did like the idea of the blog, and comments became a place to discuss. The blog was some kind of (open) forum, there were a lot of comments. I became blog addicted by that time.

Then I started to be recognized in conferences, and I wanted to stop having an eponymous blog (coincidence, or not, it was also by the time I moved to Montréal). Actually, several academic blogs are eponymous, it is rather common (we’ll get back on that later on). And that makes sense since most bloggers tend to identify their blogs, as both personal and professional. Consider for instance Ann Althouse, professor at University of Wisconsin Law School (since 1984) who met her husband through blogging (see…). I guess you can find all here life (personal and professional) online. Boundaries between professional, academic and personal life may be difficult to establish, mainly because all those aspects intertwined constantly in the lives of scholars. After a almost three years, the Freakonometrics adventure started officially.

This blog is clearly an academic blog. Because of the editor, because of the contents, and because it is now hosted by , a “platform for academic blogs in the humanities and social sciences“. It is one academic blog among many others1 . John Quiggin explained in 2006, “with the arguable exception of law, economics is the academic discipline where blogging has been embraced most enthusiastically“. This might explain why there is such an active – and enthusiastic – community (see more recently another discussion, by John Quiggin). About the academic blogosphere, Jacob Halford said that “the situation within academic blogging seems to be that we are currently a bunch of islands that are vaguely connected but not really arranged into continents and groups. We are all spread out across the digital world with a fragmented network between us.” What can we find in this community? Some economists like to use their name, like Greg Mankiw’s blog for instance (with subtitle “random observations for students of economics“). But most of them prefer to hide themselves behind a short title, like Confessions of a Supply-Side Liberal (by Miles Kimball), The Conscience of a Liberal (by Paul Krugman), or longer one, like Statistical Modeling, Causal Inference, and Social Science (by Andrew Gelman). The editor is never hidden, and we usually find a short bio, including a picture (most of the time), as well as a link to a webpage hosted by some university. Other examples might be I’m a bandit, with subtitle “random topics on optimization, probability and statistics. by Sébastien Bubeck“, or what’s new,  with subtitle “updates on my research and expository papers, discussion of open problems, and other maths-related topics. by Terence Tao“. Some blogs use puns (it is a feature that you can find on almost any blog: most of them use humor, just to explain that this is just a blog) like Hyndsight, “a blog by Rob Hyndman“. But the reference I like more is perhaps more one of those blogs where the (true) name appears, but only slightly…. In those blogs, the name of the editor appears only as the author of posts, like Marginal Revolution, where the contributors are  and , or Normal Deviate (with subtitle “Thoughts on Statistics and Machine Learning“) by Larry Wasserman (you simply have to click on the About hyperlink, but it is the only place you’ll find the name of the editor of the blog). Now, to explain the name of my blog, in a few lines, I should probably spend some time discussing a major influence.

  • How blogging started – Influences

In 2005, University of Chicago economist Steven Levitt and New York Times journalist Stephen Dubner published a collection of ‘economic’ articles, claiming that economics is, at root, the study of incentives. This is how started (the first post was published in September 2005). My blog is more about econometrics than economics, and I did borrow (not to say steal) the name freakonometrics to a colleague of mine at the Ecole Polytechnique. According to Francis Kramartz, there were two different approaches in econometric courses: see econometrics as an application of mathematical statistics, where the linear model is projection of the variable(s) of interest on the subset of linear combination of possible explanatory variables, and you derive properties, and then you discuss possible applications. Or you start with applications, with data, and then you try to find a (possibly) predictive model. Francis called this second approach freakonometrics. I find nice the maths behind econometrics (especially when you can mention geometry and projections), but I also love playing with datasets! I love the feeling you can have when you try to extract information, and think about visualization issues. I thought freakonometrics was a proper description of what will be in the blog.

Another important point when I started blogging was related to a so-called open community. I started blogging a few years after discovering R (a free software programming language, and a software environment, for statistical computing and graphics). The community of R users is based on the idea that we should share notes, codes, and tips. Since blogging is sharing some knowledge, it became natural to blog, including codes. And I have to confess that it has always been thrilling to see people willing to re-use what I’ve done in a blog post (as long as they don’t make money of it). Of course, there are alternative to blogging, such as being an active member on a forum (like stackoverflow), or answering to mailing list (see the paper by Timothy Stephen and Teresa Harrison on the Comserve experience). I truly admire contributors on forums or mailing lists. And somehow, we do the same kind of things. Except that on my blog, I am in charge.

  •  What the blog looks like ?

This might be a stupid question: since you read this post, you obviously can look around, and see how the blog looks like. On the left, I try to give a short description of my blog. I pretend that it is an “unpretentious academic blog“. It is an academic blog from its contents, not only because it is written by someone within academia. And it is unpretentious because I want my blog to be casual (but we’ll get back on this point later on). About me, I pretend to be “a surreptitious economist and born-again mathematician“. This is from my background. I did study Mathematics in France, then I discovered Economics. I got a master degree in Economics and Mathematics, and a PhD in Mathematics. Then I chose to join an Economics department, in France, for my first position, and finally got a position in a Mathematics department, in Montréal. Currently, I rediscover Mathematics, but I still love Economics. Econometrics in neither Mathematics, nor Economics. It happens to be somewhere in between. A macroeconomist will analyse and compare transportation prices. A microeconomist will try to understand why people decide to take their bike, or a car to go to work. They will try to explain why return tickets are usually cheaper than one-way tickets. An econometrician will try to get datasets with ticket price, for different dates, different destinations, etc, and then, try to quantify the price difference. Not necessarily explain it. This is what I do in my blog. I explain how to model, and I skip usually the interpretation part.

I claim that I am “a blog activist, and an actuary, too“. About the second part, in Europe, no one knows what actuarial science is, so usually, I do not mention it. In North America, it is much more popular. And yes, I am an actuary. I did publish books on mathematics of insurance, and I am about to edit a book on computational aspects of actuarial science. I am not proud of being an actuary, but the truth is, I find insurance problems puzzling and challenging, for mathematicians and economists. For the first part, yes, I keep writing on my blog that academics should blog. They do have legitimacy to comment and explain, so they should us it. I can even go on a conference on a holiday to talk about blogging !

On the right part of my blog, I try to get legitimacy. They are three different information,

I mention my academic publications since I believe they give me legitimacy, when I talk about econometric models, or probability. This is how academics judge other academics within academia.

I believe that those websites give me some credibility, not as an researcher, but as a blogger. I do also mention top site mentions, such as “100 Savvy Sites on Statistics and Quantitative Analysis“. I should probably mention that it might look like my academic profile gives me credibility as a blogger. But somehow, I have the feeling that the causality effect has changed: I now have credibility in my research because of my blog. Some editors asked me to refer some articles submitted because they read some posts on my blog (as they told me explicitly in their email). Some colleagues invited me because they know me2 from my blog, not from my research papers.

  • How do I blog, and what do I blog about ? 

My research and teaching activities are related to economics, mathematics, actuarial science, etc. I do blog about those subjects, using a less formal medium than academic journals, even if I write to an audience that I am usually talking to (students or researchers). And I cannot pretend that I write for non-economists, or non-mathematicians. Even if I want to, jargon comes naturally (even if I pretend to be casual). Different sorts of posts can be published on the blog. If we try to distinguish, there are

  • post to mention events and news
    • about forthcoming conferences, thesis prices, etc. This was done on the blog when I started, but this information is now shared with microblogging (through Twitter, via @freakonometrics). Nevertheless, there might be some recent examples on the blog, such as a PhD defense or a PhD price, or to mention the panel of the WSSF.
    • I should probably mention that I use micro-blogging to share readings I found interesting. Interesting tweets are now posted in a dedicated category, twice a week
  • posts to mention amusing situations to explain (possibly) difficult subjects
    • about game theory: when should I (otimaly) shoot at my son when playing with waterguns ? We have empty guns, we rush to fill them: the sooner I stop, the more likely he will get wet before I do (which is good, from my point of view), the longer I wait, the more water I will get, and lower the probabiliy to miss him. See also a discussion about optimal strategies to get married
    • about Markov Chains: what is the transition probability of a Markov Chain ? can I derive it in a simple case ? like Snake and Ladder game ? Here, I explained how to model that game, and how to simple Markov chains to see where you might be after rolling a dice ten or twenty time.

see also some post on genetic algorithm,

    • about demography issues: what is the age of the oldest person you know (from a TV commercial) ? How old are the popes,  or the Members of Parlements (twice actually)? Based on some open dataset, I compare the distribution of the age of MPs, and the distribution of the age of people who might be able to vote.

    • about probabililty: if I go the play the roulette, and I wish to maximize the probability of doubling my initial wealth, should I play small or should I play big ? or probability to win when playing cards : the more players there are, the longer the game? Some of the posts were published before I went to Las Vegas (for holidays).
    • about number theory, and complexity of strategies: on a Sunday evening game with kids (I pick a number, and you should find it), or a story about McGyver in an Afghan jail. In this post, I use a nice theoretical result in group theory in a McGyver story, trying to explain that yes, group theory can be fun, too.
    • about geometry: what could be the distance between points, and what are the connections with pigeonholes, is it simple to get your own Essher type graph, on breaking pieces of wood (part 1,  part 2 and part 3) or other technique to share a pizza fairly? Most of those posts are based on discussions with my kids, and I try to go further, and to illustrate difficult geometric concepts, or results, using simple discussions I had with my (young) kids
    • about magic tricks: how to sort matrix, per row. This post is based on the mathematical explanation of some magic trick.
    • about classification, and playing pétanguefollowing some discussions with students of mine, a few years back, where I suggested a dual version of a popular French sport,
    • about econometrics: based on Playmates’s measurements I try to explain the importance of working with individual observations (versus time related ones). Based on those measurements, I try to see if there is some correlation between chest and hip measurement, for young women. It turned out that there were no correlation at all, over 60 years, because we cannot treat those observations as individual independent observations, since there was a strong temporal evolution. Actually, chest and hip measurement had opposite trends with time, which tends to hide the true correlation

    • about stochastic processes, random walks (and option pricing): on the arcsine law, and drunkward’s walk. In those posts, I try to answer drunkward’s important question, and relate them to standard questions in mathematical finance
  • posts to react to articles, discovered online, somewhere else
    • about breaking records: how comes every year is the most expensive one, in terms of natural catastrophes, or about financial records. In this post, I try to see if over almost 20 years  it is an outstanding even to have 11 consecutive days were the index went down (and to compute that probability)

    • about the 100% chance of a nuclear incident called statitical certainty, about an article published in a French newspaper. In that article, two engineers explain that there is a 100% chance to have a nuclear accident, in France, over 30 years. Just by making a simple mistake in probability computation,

    • about e-cigarettes, and confusion in some French newspapper about a scientific study, where it was claimed that there was a difference, but (statistically) not significant.
    • about some probability of having an 11 hour match in tennis game, about the probability of having twice the same numbers in a lottery, or in UEFA series. In 2010, there was the longest tennis game, ever. And using some extreme value theory results, I try to estimate the odds of having such a game

    • about the traveling salesman (more a book review): inspired by William Cook’s “In Pursuit of the Traveling Salesman“, some codes were proposed to solve a (difficult) mathematical problem (in the context of collecting candies at Halloween)
    • about surveys, and pools: what does it mean if 75% of the people interviewed in a survey claim that they do not ‘believe’ in surveys, and opinion pools; and some code to predict the winner of some elections (based on several pools)
    • about insurance and bargaining: why is it – sometimes – rational for insurance company to bargain, with their insured, based on some old research paper, published in the 70’s.
    • about financial issues: what does that mean the a financial stock is hold, on average, 8 sec. ? what would a bunker full of gold be like, how large can it actually be. It started a discussion about the (difficult) estimation of what should be a (simple) average time
  • posts to discuss a question asked by a student, or a colleague, that puzzled me (it is then more a discussion, without answers)
    • about the interpretation of a parameter in a model: can weights in weighted least squares be understood as a frequency ?
    • about subadditivity and risk measures: why statements in discussion papers regarding Insurance company solvency might be incorrect, and yield to counterintuitive situations.
  • a presentation (and if possible an explanation) about a paradox,
    • about the Monty Hall paradox (see also a discussion about a similar topic on computing probability with respect to some information or more funny)
    • about Simpson’s paradox, and pies choice,
    • about bias selection: why we should not listen to students and policemen (see ) or why are there always more buses on the opposite side of the road.
    • about probabilities, like nuns and Hell’s angels in an airplane, some nice puzzles, here and there, and probabilities to have brothers and sisters: do boys have more brothers, or more sisters?
    • about events that will occur at some infinite time, with a strictly positive probability
  • posts to share some experiences with students (or by myself) to investigate a model, a dataset, or a computer function
    • about airline tickets: when it is optimal to buy – online – an airline ticket. I did use a dataset mentioned in a study on a similar topic, and I try to explain that this question is related to some risk aversion measure: are we looking for the date where, on average, the price is the lowest, or a date were, with 90% chance, the price is the lowest?
    • about graphs: with Ewen Gallic, what are the connections among twitter accounts of Members of Parliament (in France). The idea was to learn how to play with Twitter API, and to get a nice visualization,

There was also a post on hours of tweets (where I tried to see how long I can survive away from Twitter).

    • about graphical functions: finding Waldo in a picture, using the red and white stripped shirt , or enclaves in maps. Discovering image treatment functions
    • about circular density estimation: how to make sure (for hourly data) that 23:50 is close to 00:10 ? that (for spatial data) that -170 degrees (west) is close to 170 degrees (east) ? with application on earthquake location, or calls to 911. Actually, for 911 calls, the first post was entitled “minuit, l’heure du crime“, where I did try to figure if there were more crimes at midnight (which is precisely the time of discontinuity),
    • about textmining, and letter appearance in language (and books): including La Disparition, a book written in French with no E (how different is letter appearance probability, compared with the conditional one, when E is removed?). Discovering textmining functions.

see also text extraction from tweets,

    • about first names, in France, per year. Using counts of birth per first name, region, and year, I try to get visualizations of spatial and temporal patterns associated to some common first names,
    • about car speed, or car accident (based on some dataset I got). I try to study the links between the speed of two consecutive cars (following a discussion I had with my wife while I was driving, where I try to explain that if I drive too fast, it might be because the driver in from of me is driving too fast),
    • about sharing datasets: we did generate a dataset linking zip codes and spatial coordinates or with counts of births in France, per day.
  • posts with a more historical perspective on a theory I discuss in a course
    • about the history of extreme value theory:what is the story behind the Fisher-Tippett theorem, and the law of three types, with Gumbel, Weibull and Fréchet distribution ? Did those people (really) work on extreme values ? Who got which result ? See also the history of the return period concept.
    • about the Student t test: who is this Student, and what are the connections with Guiness ?
    • about the chi-square distribution: what did Peason discovered first, the chi or the chi-square distribution ?
    • about discounting: Leonardo Fibonacci and discounting
    • about the law of small number: why is the Poisson distribution so important ?
    • about financial market efficiency (in French): who said that assets prices could be modeled as random walks (and therefore are then ‘purely’ random) ? What is a martingale ? See also an application to temperature time series in Montréal.
    • about optimization: did Newton and Raphson (from the so called Newton-Raphson algorithm) really invented the gradient descent ?
  • codes, references and slides related to some courses, conferences or research papers

    • about demography: codes and tables generated for the Appendices of a book on Bodily Injury, Insurance and Legal issues,
    • about climate change: codes and graphs related to a talk given a Lyon on extremal events, and climate change.

  • a more general discussion, about science and dissemination (not to say teaching)
    • about teaching computer codes to kids: on hacker generation, and why kids should learn how to code
    • about research mythology: how journalist discuss research issues (based on two experiences)
    • about humanities versus sciences: visiting the Gugenheim museum in NYC versus MoMaths (Museum of Mathematics), with kids


  • How do I blog, and what do I not blog about ? 

Now, I should admit that I will not blog on all topics. For instance, I was involved in some discussions, where a student of mine asked interesting questions, about religion and education. I wanted to share things I’ve heard (actually, read), but a lawyer told me that I should avoid to do so. And I know there are things that I should not post on my blog if I do not want to ruin my career. So for legal issues, there are things that I will not write on my blog. And similarly, I try to avoid libel actions, so when I write that someone published something stupid in a post, or in an article, to try to say that as nicely as I can. Again, I claim that my blog is “unpretentious“, so I am not here to fight, nor to be preachy, just to have fun! As we’ll discuss in a couple of paragraphs, I do fight every morning on my bike, I do fight when I arrive at work. My blog is still a peacefull place, and I want to keep it like that…

Another reason why I will not blog about everything is that I do not have legitimacy to blog on everything. I mean, I know a bit of mathematics, but when I post something about a property in geometry, I feel like an impostor. Similarly when I write something about some history of some statistical concept, about regulation in insurance, about simple game theory result, etc. I try to publish on topics that are either related to my research, or to my teaching activities. Even tonight, when writing this post, it looks like a big fraud to me, and I find it extremely hard to write some exegesis about my blogging activity.

Finally, I should confess that I do not blog about everything because I try keep some ideas for my research, that will (hopefully) end up with a publication in a peer-reviewed journal. Blogging does not get much credit in an academic career, let’s be pragmatic… Blogging is not a substitute for other academic writings! But they can clearly coexist (see a discussion on insidehighered blog). If we compare a blog post and a (standard) academic article, it takes more time to write a paper, mainly because full referencing is necessary, because it is necessary to convince the editors, as well as referee(s) that you wrote something original, that is probably a major contribution. It is much faster to publish a post! And probably most important, while blogging, you can explore a question, you do not need to answer it.

  • How do I blog? Somewhere between an academic paper and a journalist article?

As mentioned previously, some academics do publish posts in blogs hosted by newspapers, such as The Conscience of a Liberal (by Paul Krugman). Somehow, those journals (here the New York Times) host academics the same way newspapers hosted some opinion pages, were academics where invited to give their point of view, a few years back. But, as John Quiggin explained in 2006, “newspapers are generally reluctant to repost on academic working papers and similar publications unless the conclusions are obviously newsworthly“. Economics in newspapers has to be related to macroeconomics, and science has to be related…. to medicine or technology (the science page is now a nice advertising page for the most recent smartphone applications, or the electronic cigarette, as mentioned previously). And, as mentioned by Robert Cottrell, a couple of decades ago, experts (not to say scholar) “have functioned as sources for newspaper journalists. Their opinions would emerge often mangled and simplified, always truncated, in articles over which they had no final control.” Now, with blogs, it is possible to read them directly, in a style that is easier to understand, compared with academic (standard) publications. “The general reader has access to expertise that was easily available, a decade ago, only to the insider or the specialist“. Writing a post is an academic blog is neither pretending being a journalist, nor writing an academic article. In the traditional process of research, we discuss with colleagues, possibly in conferences, but only the final publication remains. False starts and heuristics are skipped, because they might appear as un-necessary to get an understanding of the article. And I truly believe that this is exactly where blogging become interesting.

Why am I still blogging? and why I will probably do it for a long time…

  • Why am I still blogging ? a peaceful island within academia ?

One of the main reason why I am still blogging after 6 years, with enthusiasm, is because it is still a lot of fun. And it is a place that I appreciate all the more that academia is currently a nightmare. I might sound incredibly cynical (and I have to confess that I think I am becoming cynical), but I interact with the blogging community because I want to. I interact with students and colleagues because I have to. There are two important issues in academia, when talking about money: tuition fees rise, and the decrease of public funding for research. I have the feeling that (undergraduate) students, are consumers. And consumers are the real bosses, you know that, right? And as a professor, I am like the seller in the store. I can try to give some advice, but I am useless. Most of my students are no longer interested by the story behind a model, they want some recipes for their future job. They want to know what to use, and when. And since universities evaluate their professors, they ask students to fill evaluation forms. And professors do everything to get good evaluations. That is a simple and extremely rational game. And about the colleagues, I can tell you so many stories, that I have experienced, or heard about. Everyone is now suspicious. And again, it is rational. The less money there is to do some research, the more competition. It there are one or two grants in my field of research, in Québec, I have no more colleagues and friends, I have only competitors. This is not (only) a feeling I have, it is truly something that I observed. Many time, I have been with colleagues, and we’ve been working with doors closed, not because we did not want to get disturbed, but to avoid that someone still our idea. We’ve even been to work in some coffee, outside the university. With students, it is a commercial world, while with colleagues, it is a world of paranoia (most of the time for good reasons). I always find odd, when I fill a form for a grant, the section about my ‘main contributions‘. When I arrived in Canada, some colleagues were paternalistic (one more time for good reasons) and they told me that I had to mention the impact of my research. Like my research could save the world, or help to cure from some awful diseases… No, what I do is theoretical, probably useless, and I cannot expect too much. Unfortunately, I am not Alvin Roth (who proved that mathematics can save lives, literally). And yes, when I have three consecutive hours to do some research, it is probably because either I missed a course, or because I forgot about a meeting…

Compared with those (standard) academic activities, blogging is fun. Within the blogosphere, I do not see competition, just motivation and stimulation. You can interact with other bloggers, learn from them, and so far, it is still a pleasure to blog. Some bloggers claim that it is a shame that blogging is not recognized (formally) within academia, but I think it is actually a great opportunity. We do blog because we want to, it is not another required task. So it can still be fun… And when talking about the impact of my activities, I believe that my blog has much more impact than my teaching (in a class room) or my research.

  • Why am I still blogging ? who I am blogging for ?

I have to confess that I blog mainly for myself, in the sense that I do not want to have a readership waiting for me to post something everyday! Also in the sense that my blog gives me a complete freedom to talk about things I find fun, with a whole person style (and actually I do use my bog to develop my own “writing voice“, to use Jill Walker’s words), discussing about personal issues. I remember when I started blogging. At first, I thought that no one was reading my blog, and then friends, colleagues told me that they were. It is actually thrilling (not to say scary) to have 5,000 readers for a blog post, when you think about the number of readers of academic articles. As claimed by Brendan O’Connor, “blogs are a more effective medium for intellectual influence than journal articles“. Somehow, it looks like academic journals try to avoid exposure. I mean, publishing an article in the Journal of Narrowly Focused Hyper Specialized Field Studies is a great place to hide your research.

If I wanted to be provocative, I would say that research is a social activity, where we need to keep, and to create, interactions with various researchers, reading papers, keeping our mind open. On the other hand, blogging is definitively a personal activity. And since I am an old bear, usually reluctant about standard social activities, blogging is perfect for me.

As mentioned in some previous posts, I use my blog as a note book, to keep traces of ideas, codes. So yes, blogging is personal. But it is opened, and anyone can access it. So I use my blog to promote my work, and my scholarship. Using Melissa Gregg‘s quote, I see academic “blogging as conversational scholarship“. Blog are great to encourage conversation! Blogs are coffee house (in the sense of XVIIth Century, in England). In blogs, we connect to other blogs, using comments, reactions, and hyperlinks. But actually, Derek de Solla Price explained in 1963 (see e.g. Doug Horne’s paper) “the prototype of the modern scientific paper is a social device rather than a technique for accumulating quanta of information“. So having informal discussion is probably the best way to work, as an academic. This is also the idea of Diana Crane, “the growth of scientific knowledge is a kind of diffusion process in which ideas are transmitted from person to person“. Using blogs, we can develop and connect a network of various people, from PhD students to practitioners in the industry, as well as more experienced academics who might share common interests. The blog is read by students, former students, colleagues, probably the dean, and even the department secretary. My kids too, someday…

  • Why am I still blogging ? cost-benefit analysis

With a simple cost-benefit analysis, I will probably blog if benefits are more important than costs. One component is related to time issue: is blogging costing, or saving time? I receive frequently emails, asking for explanations on a technical question (from students, former students, or anyone actually) that will need a  detailed email answer. I still believe that a “reply to public” is possible, with a blog post. Similarly, while teaching, the same question is asked twice a year. The first year, I can write an answer in a blog post, and then, I can integrete it to my notes (blog posts can even be more interesting than lectures notes). I cannot believe that blogging is a waste of time, since I see my blog as a long-term memory (I do have an extremely short-term memory, unfortunately). And just to be naughty, I do see a lot of academics that “do not have time to waste blogging” who can write extremely long, detailed (and most of the time, nicely structured) replies. If I write a detailed reply to a specific question (because I found the question interesting) I find it stupid not to share it. All the more because other people might also be interested in interacting… With blogs, dissemination is immediate, as well as comments and feedback.

A lot of researchers within academia still reject blogs because they’re not serious, and not peer reviewed. Not serious, I can live with it. I am a big fan of the Ig Nobels prices: yes, we can do serious research without being too serious. But rejecting blogs because they are not peer reviewed… you’ve got to be kidding me! Comments are open, and unless you want to sell Louis Vitton bags or Viagra, I publish all of them. In blog, comments can be more constructive than comments you get from referees in a so-called peer reviewed journal. Blog posts are published on the (open) web, not in some journal so expensive that no one can actually read it. Yes, commenting is not a formal or rigorous as a peer review publication, but having opened comments may contribute to establish quality and credibility of a blog. Having comments from the community is a great benefit. Further, blogging is interesting since I believe it did improve my teaching. In the sense that writing posts helped me (many times) to clarify my ideas. And I believe that my lectures are then better. So I guess I will keep blogging for a long long time…

I guess I will stop here, even if I might have tons of other things I would like to add. Based on this post, I now have think of something interesting to share in the panel, next week. But I also have to keep in mind “academic blogging can be an important medium, when it avoids the meta-narcissistic onanism of blogging about how important academic blogging is”, as claimed by Chris Parr.

1. To mention only some of them, see Edwin Chen’s, Michael Giberson and Lynne Kiesling’s, Christopher Long’s, Josh Hendrickson’s, Rob Hyndman’s, Andrew Gelman’s, Christian Robert’s, David Stern’s, John Cook’s, Greg Mankiw’s, Mark Thoma’s, Tony Cookson’s, John Mount and Nina Zumel’s, John Myles White’s, Bill McBrid’s, Alex Singleton’s, Liyun Chen’s, Eeshan Malhotra’s, Percy Beach’s, Miles Kimball’s, Brad DeLong’s, Honglang Wang’s, Matt Asher’s, Cosma Rohilla Shalizi’s, Denis Haine’s, Dimiter Toshkov’s, Christopher Gandrud’s, Jodi Beggs’s, Eric Nguyen’s, Matt Bogard’s, Andrew Ziem’s, Dave Giles’s, Jeff Ely and Sandeep Baliga’s, Tyler Cowen and Alex Tabarrok’s, Kevin Bryan’s, Eran Raviv’s, Gianluca Baio’s, Ulrich Matter’s, Gregor Gorjanc’s, Nate Silver’s, Jesse Anttila-Hughes and Solomon Hsiang’s, Francis Smart’s, Corey Chivers’s, Steve Walker’s,  Sebastien Bubeck’s, James Hamilton and Menzie Chinn’s

2. I won’t have time to discuss this point today, but I have been discussing with a lot of persons who truly believe that they know me because they read frequently my blog. And, to be honest, that might be true, and it is a strange felling. I mean, I remember some diners where people told me that they’ve been on my blog, and they remember what I did post, and I am like “great, but I don’t know you at all… I have never read any of your research papers, I don’t know what you might be working about…” This asymmetry put me in some awkward situations.

Blogging in Academia

In a few weeks, I will attend the World Social Science Forum, and participate to a panel committee, on “Minor forms of academic communication: revamping the relationship between science and society?” The Forum will take place at the Palais des Congrès in Montréal.

First developed by physicists, the open access movement has significantly widened in scope and has been taken up by the European Commission and the G8. If the motivations behind this are essentially to do with innovation, competiveness and the economic efficiency of state investments, open access also introduces a major change in the relationship between science and society. Once citizens have access to the results of social science research, in real time and in their entirety, the whole nature of the relationship between science and society is renewed. However, the debate is focused on the major forms of academic communication: journal articles and books. And yet, in ways almost invisible to the academy, so-called minor forms of academic communication are developing in the interstices, creating a kind of “permanent virtual seminar” and intermeshing with promising heuristic, pedagogic and societal possibilities. Over the last decade, research blogs have embodied a new experience of academic communication, allowing for an experimentation of formats, schedules and interactions that differ from those of the traditional academic process, at both its early and later stages. These blogs dovetail with societal questions, open up new frontiers and step outside the academic ivory tower. From “just-in-time sociology” to probing interpretations of the “Arab Spring”, from analysis of contemporary visual culture to knowledge of contemporary movements such as rap, tattoos and religious conversions, academic blogs place the social sciences at the heart of the society they study. Academic blogs have already found a following. Through this readership a democratisation of access to science is underway. This momentum brings opportunities and reveals new ethical, epistemological and scientific questions.

See also and

For an academic, imparting knowledge revolves around two main activities. As a researcher, an academic must produce articles destined for a very limited readership and adhering to a very rigid process, one that involves severe constraints of time and form. As a teacher, an academic must think of his or her students; he or she must make knowledge accessible and arouse curiosity while also seeking to instil the notion of scientific rigour: outlining hypotheses; identifying the results that may be obtained if these hypotheses are borne out; questioning the validity of the said hypotheses. I will come back to the experience of the Freakonometrics blog, which originated as a response to a pedagogical difficulty and is based on two recent ventures. The first was Freakonomics, Stephen Dubner and Steven Levitt’s blog (then books), which aimed to explain economic behaviours using surprising and sometimes provocative examples. The second was the recent explosion of “data visualisation”, an offshoot of open data and big data that showed statistics could be elegant as well as informative. The Freakonometrics blog emerged from a desire to explain in very practical terms how econometric modelling works, by providing (or explaining how to find) data and sharing codes with which to produce graphics. This experience provided the opportunity to publish research studies in an unconventional form. If the rigour expected is the same as that of an article submitted to a peer-reviewed journal, the blog format allows authors to include anecdotes and exploit the rich potential of online documents (animations, links, etc.). Blog posts also extend the notion of reproducible research, the idea being not to impress the reader by making him or her think (s)he is reading something groundbreaking (which we all seek to do in an academic article), but instead to instil the idea of do-it-yourself by allowing all readers to reproduce the analysis.

My paper will discuss the creation of a blog on the Hypotheses platform in relation to my position as a “young academic” and drawing on my experience of academic blogging. I would like to put forward the hypothesis that for a young academic, blogging is a means to liberate oneself from the rules of the academic world. It offers unrivalled editorial freedom and potential academic recognition. I would like to show that, in turn, this academic liberation emancipates knowledge itself, allowing it to reach sectors and readerships beyond those originally intended. I also wish to point out the practical aspects of this interplay between the liberation of the young academic and the liberation of knowledge. First, I will show why for a young academic, blogging is a way to liberate (or at least distance) oneself from the rules of the academic establishment. Secondly, I will attempt to show that by freeing themselves from the academic sphere, young academics impart knowledge, skills and qualities that are useful to everyone.

In a context of financial difficulties and waning influence, the social sciences now place more importance on producing authority than producing knowledge. The new tools of digital micro-publication, which compete with traditional publications yet lack institutional legitimacy, have met with strong resistance. The characteristics that make them such formidable tools for research, communication and academic discussion, and for collective and collaborative work in particular, remain largely unrecognised. In the absence of suitable incentives and training programs, use of these tools is developing virally and falls far short of full potential. Will such tools continue to develop as best they can at the sidelines of the academy? While the humanities shun their social responsibilities, academic blogging will remain an art rather than a science.

See also

  • A blind spot? Digital infrastructures for digital publishing, and for academic blogging in particular, Marin Dacos

After several centuries of development, knowledge technologies today form a highly organised ecosystem, structured around books and journals and with its own clearly identified professions, infrastructures and actors. From publishers to librarians, authors to booksellers, a book industry has emerged and encourages the circulation of ideas. With the rise of the network, these roles are slowly being redefined and new actors are rapidly emerging. The 2006 ACLS report (“Our Cultural Commonwealth: The Report of the American Council of Learned Societies Commission on Cyberinfrastructure for the Humanities and Social Sciences”) is one of the first signs of recognition of the need for digital infrastructures. These infrastructures are not simply confined to “noble” publications i.e. books and journals. They also concern the so-called minor forms of academic communication. Yet developing such infrastructures requires much more than simply installing a server under a desk. On the contrary, digital infrastructures necessitate the creation of platforms, which in turn entail the emergence of new teams and new professions – those of digital publishing. These platforms are often developed or bought up by predatory multinationals (for example, Mendeley absorbed by Elsevier). Academic-led alternatives do exist (Zotero for bibliographies, Hypotheses for blogs), yet the academic community has failed to fully recognise the associated opportunities and risks. The academy has every interest in making sure it does not become marginalised within its own infrastructures. The alternative is to reproduce the vagaries of the extraordinarily concentrated global publishing system, which has stripped the research sector of some of its intellectual and budgetary initiative-taking capacities.

See also :  ”Scholarly blogs, a space on the side for academic dialogue” by Marin Dacos and Pierre Mounier. Part 1 and Part 2.

(to be continued…)

Quiet “holidays”?

People outside academia often wonder what we might be doing when we do not teach. And actually, my teaching session ended on May (I do include time to grade). So am I on holiday?

I have to admit that starting last Tuesday, everything looks more like holidays, since the kids started their own. Even if I have to prepare lunch boxes, it is not the rush to go to work. And they like to go to bed late (or at least later), we did enjoy the Jazz festival this weekend, this week it will be the Circus festival and we plan to see the fireworks contest, and when we’re not downtown, we also enjoy going to play basketball at the playground next door. So yes,it might sound like holidays…

But even I feel more relaxed, I do work. And to be honest, I feel extremely busy. Which might explain why the blog was so quiet those past days (actually, since the kids are – also – busy, I do spend time to upload pictures and videos on their own blog… more time on their, less time on mine).

At the beginning of this month, we were working with Ewen on the paper (now submited) and the poster (he did won the poster contest at the R conference in Lyon, congrats Ewen) on smoothing densities on maps. I am also trying to finish another couple of papers I would like to submit (at least to post on before going on holidays. I am also working with colleagues from the SoA (I was in Chicago mid-June, since UQAM is a center of excellence, and I will be in Atlanta mid-July to work on the new general insurance track), and also working with (and for) students. Trying to send emails to make sure we’ll get our datasets in September, for instance. I have also admistrative duties, like making sure that colleagues I should be working with in August will find a place to stay when they will arrive in Montréal. I also have to plan skype meetings with co-authors, to see where we are on our projects, before having a break, planning what should be done when we’ll be back, mid-August, etc.

But what keeps me really really busy is the book I am editing. I spend time reading contributions, trying to unify notations and concepts, making sure that references are correct and relevent, etc. I am in the flat part of the productivity curve. Time when spending 1 full day on a chapter will generate 5 new pages is over. On 1 full day, I can simply fix a few typos, change a graph, find a nice reference. It is long. And painful. But in two weeks, we should have a preliminary version, that we will all cross-read, including colleagues who told me they were interested to have a look at it. In two weeks, I will be off! And I really need that break!

Eat a beaver, save a tree

Wednesday, just before leaving the office, I remembered I wanted to buy Andreas Kyprianou’s book, on Lévy processes. A second edition is coming soon, but I just need a simple introduction to Lévy processes, so I thought that this first edition should be complicated enough for me. And when a second edition should appear soon, you can get a discounted version of the (almost) old one. So I went on Springer’s wesite to purchase the book. I did pay for the book, and finished packing, in order to go back home. I did receive my confirmation order, which is standard, and I opened it,

Wait! “eBook“, “Download PDF“? What does that mean, I thought I was buying a book, like those we can hold in our hands…  Indeed, on Springer’s wesite the default version seems to be that eBook, and you have to look, in the back, to get a Softcopy, which should mean a hardcopy with a softcover. I have to admit I started to freak out. I never buy eBook! I am extremely old fashion! Those who know me know that I even print pages from the internet to read them! Anyway, I sent emails to all possible contacts I could found on Springer’s wesite, trying to get in touch with someone who can cancel my purchase. I mean, I did not download to PDF, so, from a technical point of view, each customer does have a dedicated link, and they should know I did not download it! So, until I download the PDF by clicking on the link, somehow, I do not have it, right? So I did ask them to delete the link, refund me, and then I will get back on their website to purchase the book (after two days of discussion by emails, they keep telling me I did buy a book, so I have to admit that I do not know which word I should use to describe that antique object made of paper). Actually, when I said that I made a mistake, that I just wanted to return the product I did not consume (I do not know how to return a link actually), that I wanted at the first place to get a paper copy of the book, I got that legendary answer,

Dear Arthur Charpentier,

Thank you for your email and interest in our products.

This is to inform you that it is irrelevant for us to proceed with your request, because it has already been entered into our database/system.

However, when you have downloaded the PDF copy of the E-book. You can print manually through your printer.

If you want a paper copy of a book, “you can print manually through your printer.” At first, I thought it was some kind of misunderstanding. Or joke, maybe. But no. You cannot cancel a purchase when you order eBooks. And to make sure that I got the book, they did send me the full pdf in my mail box. What I am supposed to do with that file? This is not what I wanted! I wanted a book! a book with paper you can hold in your hands! with paper, made from trees that died so that I can learn stuff!

Anyway, I gave up… I will ask colleagues if I can borrow their copies. Now, I have to fight with Dell since I ordered a laptop (yes, the Ubuntu version), and it did arrive at the office in a wet box. Looks like the computer (at least the box) has been staying in the water for a very long time! I don’t know if people around still believe that researchers actually do research when they have time… trust me, they don’t! They discuss with Customer Services… and it can take a while!

Bayes, credit scoring and terrorism

Once again, my neighbor Corey did publish a very interesting post on his blog… on how likely the NSA program will catch a terrorist (a real one). I was working on something similar last weeks, with Stéphane Tufféry, for our chapter, entitled Statistical Learning in Actuarial Science. The idea was to show credit scoring techniques, from logistic regression, classification trees, random forests, etc. Of course, it is more boring, since we talk about loans and not terrorism. In credit scoring, we consider possible loans, and we have to predict if someone is more likely to be a bad guy or a good guy. The idea is the same: based on some covariates, we need to build a score function, that can be related to the probability of being bad. The higher the score, the more likely the person will be a bad guy. Then, of course, we have to discuss errors, namely false positive (good guys that we think are bad) and false negative (bad guys that we think are good). From the company, you do not want to have bad guys in your portfolio, and from everyone else point of view (since everyone believes he is with the good one, this is a classical optimistic bias), we do not want to be confused with those bad guys. Then we can spend hours on classification curves, and criteria to assess if our classifier is good or not, etc. While I was writing the introduction of the chapter, I remember that I found it hard to find proper words (to describe that 0/1 problem). But I did use (like everyone else) the terms good and bad. Like in terrorism. Except that to use this terminology (bad and good), we have to be more specific. In credit scoring, a bad guy is someone who did not pay back, at least once, for instance. But in terrorism, I think it is more difficult to say what a terrorist is.

I mean, in France, we did experiment terrorism too, a few years ago. In December 1996, I was in a RER train, going South, and we reached Cité Universitaire when a bomb did explode in Port Royal. The train following mine I guess. I remember that a couple of days after, I was traveling Paris, in bus, carrying with me a nice plant of… a plant that you’re not supposed to grow. Say I was carrying sandwiches, according to Ted Mosby. So in order to avoid troubles (since I was not suppose to have this kind of plant species), I put it in a large box. I remember that people were starring at me, and some actually asked me what was in the box. So for some reasons, people try to build there own terrorist classifier, based on what they think might be covariates. And dirty trousers, not well shaved, long hair (yes, I used to have long hair) and box in the bus were obviously some of them. Note that I don’t blame them, I do the same! After reading Corey’s post this morning, I took the bus. And I saw someone with a ninja sword.

At first, my terrorist classifier put her (yes, I try to have a gender-free terrorist model) in the bad guy class. Then I understood it was an umbrella. So I put her in the super cool geeky category (that only a few can reach).

When I started to teach non-life insurance in Paris, the last part of the course was dedicated to large risks, natural catastrophes, and a hot topic: terrorism. I was giving this course (probably my best experience, ever) in tandem with François Bucchini, who was working by that time for AXA France. The two of us were giving the course together, interacting: I was the boring guy doing the maths, and François was sharing his experience. And by that time, he was involved in the creation of GAREAT, a market structure, launched in France in 2002, to propose reinsurance against terrorism (for French companies). And one of the first claim was from the CAV (which is a pun for Comité d’Action Viticole) considered as a terrorist group. So, as he told us, be careful of prejudices when you think about terrorism. Cool wine drinkers can be dangerous terrorists…

Actually, I would love to see covariates used by the NSA to predict if you’re a bad guy, or a potentially dangerous terrorist. Let us have a guess… You have asked for a visa for Pakistan? or Afghanistan? or Libya (not Libya, not yet bad guys still have good friends there)? You have a NRA membership? You bought some heavy metal on iTunes? You still have a stop acta sticker on your blog? you have a blog? you wrote a post including the word terrorist in it?

Note: I am supposed to be in Chicago next week. Si if I cannot enter in the U.S., we’ll probably know more about potential covariates.

May the 4th (be with you)

Today is a special day, for all us who did grow up with Star Wars,

And on the internet, one can easily found serious posts, related to Star Wars, for instance, a series of posts on quantifying Stars Wars, with part I,…, part II,…  and…, and finally part III,…, for statisticians. One can also read a nice post on Star Wars economics,…