With this post, I bring this blog to an end. Not that I want to stop blogging altogether – the experience of these years has been interesting, funny, rewarding. But I feel it’s time to move away from the personal-diary-of-a-researcher approach I have had so far and adopt a more focused, thematic approach now. So, I’ve decided that I’m going to move forward into the world of data. My new blog is called “Data Big and Small” and you can find it here. Hope I’ll see you there next time.

How come opinions and ideas can remain the same for long, even when people come and go? even when those who initially held those ideas have left? This occurs most frequently in organisations, which can display distinctive and persistent opinions, orientations and ideas despite turnover of members.

Juliette Rouchier, Cécile Emery and I have been exploring the conditions under which this can happen. Take an opinion, defined in the broad sense of shared understandings on a matter that is relevant for an organisation’s activities, and on which members have some degree of discretion. Clear enough, but how to model it?

Now, we were fortunate enough to be able to rely on an already well-established literature on how opinions such as political extremisms, can spread in a population. The usual assumption is that people change their views through social influence: if I talk to someone, I am inclined to change my mind, albeit perhaps only slightly, as a result of the conversation. This doesn’t always happen of course: my interlocutor will influence me only if our initial opinions are already somewhat similar (for example if I’m a convinced leftist I can be affected by another leftist or even a moderate, but certainly not a right-wing extremist).  Guillaume Deffuant, Frédéric Amblard, Gérard Weisbuch and Thierry Faure developed in 2002 a very insightful model of how this simple rule, if consistently applied to a population, may explain the spread of extremisms from small, marginal groups to a large majority. Under given conditions, one can observe the emergence of a consensus (everyone holding the same opinion), of polarisation (for example a right-wing and a left-wing group that won’t make any concessions anymore) or fragmentation into multiple opinion groups. Their model, developed with agent-based computer simulation, has been highly influential and many researchers have refined, improved, and applied it before us.


Continue reading ‘Ideas persist, people come and go…’

DataIt is at least the third time I am confronted with this problem – submitting a proposal to a funder, being unsuccessful, and not being told why. Is my proposal flawed or is it simply addressing a topic that is less of a priority for them? And if it is flawed, is it because of its scientific contents or its project management plan? To what extent did my (and my collaborators’) past career affect the decision? I am sure all others in my job will have experienced similar frustration at least once… and my feeling is that this is becoming more and more frequent.

Applying for research funding should not just be like buying a lottery ticket – funders, whether public or private, national or international, should play a much more important role in advancing knowledge and supporting the research community. This should include, I believe, helping unsuccessful applicants understand what was unsatisfactory and how they could improve their ideas. This would be a way for funders to contribute to raising the quality of research above and beyond what their (necessarily limited!) financial means allow.

For all their inadequacies, peer-reviewed journals do this: I never got a paper rejection without a justification, even when it was just a quick desk rejection. However disappointing at first sight, in the long run well-motivated rejections can be highly helpful for a researcher.

Why, then, do so many grant givers refrain from following similar rules? Some say they have limited resources and cannot ask too much of their administrative staff and reviewers. But journals lack resources too: they largely rely on fellow academics acting as unpaid volunteers, and yet they do offer this help to colleagues. (Well of course journal publishers are known to have fat incomes, but this is another story – better leave it aside for now). More seriously, many funders report being snowed under huge numbers of applications at single deadlines, once or twice a year – way above what the average journal would expect – so that refusing to provide feedback is a way for them to cope, ensuring the whole process takes a reasonable time.

In a long-term perspective, however, I insist that providing feedback would still be a better option than holding it back – as those who are unsuccessful at their first application will know whether there is any hope for them to improve the proposal and succeed at some future call, instead of just re-sending it blindly at any possible deadline. Applications, over time, would become more self-disciplined and overall, of better quality.

But there seems to be also an underlying issue with public funding of research more generally, and with research not specifically Poundsear-marked to a project for which a dedicated stream of funding is absolutely necessary. General research money is less and less available in our institutions (I can speak at least for France and the UK, but I’m sure other countries would fit the picture too…): it becomes more and more difficult to fund work for small projects, single papers that do not require massive data collection or analysis, follow-up work on previous projects, or pilot studies. As a result, more and more researchers apply for project-tied funding, but not all of their research can be disguised to look like a well-defined project – hence, the volume of applications reaching funders explodes and their quality and suitability go down.

Funders can do better, but governments and research ministries should do better too – not placing all the responsibilities on single funding agencies but providing the basic resources that keep general research going.

A new article of the ANAMIA team (notably Antonio A. Casilli and Lise Mounier, and myself) has just been published online in the journal Field Methods. It is entitled Eliciting Personal Network Data in Web Surveys through Participant-generated Sociograms, has methodological focus, and targets primarily a public of social science researchers.

The article presents a method to elicit personal network data in Internet surveys, exploiting the renowned appeal of network visualizations to reduce respondent burden and risk of dropout. It is a participant-generated computer-based sociogram, an interactive graphical interface enabling participants to draw their own personal networks with simple and intuitive tools.

We used it in our ANAMIA study of users of websites on eating disorders. In it, we have embedded the sociogram within a two-step approach aiming to first elicit the broad ego network of an individual and then to extract subsets of issue-specific support ties. We find this to be a promising tool to facilitate survey experience and adaptable to a wider range of network studies..

The tool is presented in a vidéo accessible here.

Back to life…


Oh it’s embarassing… it’s been ages since I wrote my last post… this is really against all my new year’s good resolutions! And work is not even an excuse – there’s a lot of it of course but it was just the same last year, and I didn’t perform so badly as a blogger. Or perhaps it’s because I have been too busy moving home (twice, both in my Parisian and Londonian lives…). But that’s an uncomfortable hypothesis –suggesting that, well, those who thought ten years ago, that there is a trade-off between online and offline activities, were not so wrong after all… and we thought this was just an outdated view! So perhaps I simply have to admit that I just didn’t manage… But yes, I promise I’ll be back to life from now on – I haven’t stopped thinking about data, networks and so on throughout these months, and I have some ideas I would like to write about!

More soon,


I am late, I know… I came back last week from the NTTS (New Techniques and Technologies for Statistics) 2013 conference in Brussels and have not yet had a minute to stop and write down my impressions. Fortunately I live-tweeted during the conference, so I haven’t completely lost trace of my thoughts while there… let me try to put them together a bit more coherently now.

TouchGraph4NTTS is a bi-annual conference of official statistics – those institutions and people who provide governments with essential quantitative information about society and the economy. Key actors include Eurostat and National Statistical Offices of countries, sometimes statistical agencies of particular ministries or government departments, as well as international institutions that also produce data such as the OECD, and academics. Official statistics used to work primarily with surveys – asking citizens and firms to report on their habits, activities, situations. Examples are the Labour Force Survey, or the Survey on Income and Living Conditions, both conducted throughout the whole of Europe. Northern European countries initiated the tradition, now adopted by an increasing number of European countries, of supplementing surveys with administrative records: official registers of vital events such as births, deaths and marriages; tax returns filed with the fiscal administration; registers of attendance in public schools; admissions to, and discharges from, public hospitals; and so on. Administrative data have the advantage of being already available, with no need of bothering people with forms to fill; of being abundant  and sometimes even exhaustive; and of being very detailed and often much more accurate than any recollection by individuals. Traditionally, economists in particular have always being suspicious of surveys, and much more inclined to trust administrative data which suffer much less from any respondent-related cognitive or memory bias.

But Big Data are now shaking up this long-established world of surveys and administrative records. Very different, very promising, and typically produced by other actors (notably private companies rather than public-sector services), Big Data seem to question the existence and usefulness of more traditional data sources. Big Data are digital traces of our activities, collected by the electronic devices we now all use: our Internet usages, Facebook or Twitter accounts, credit card purchases, loyalty schemes with companies (like frequent flyer programmes with airlines, or customer rewards cards with supermarkets), use of public transport as recorded by our cards (such as Oyster in London or Navigo in Paris), CCTV films etc. The sheer amount of these data, the level of detail and the accuracy of the information collected are appealing: my credit card statement certainly provides a more precise account of my expenses of last month (when, where, how much, for what…), than what I may recollect even with my best effort. Companies see a lot of potential in use of Big Data (see the 2010 The Economist report on Data Deluge, or the 2011 McKinsey report, presenting Big Data as the next frontier for innovation) researchers are enthusiastic, and even public administrations now start realising this is a seachange.

Continue reading ‘Statistics and Big Data’

Just as an additional part of my interview on data has come out on SFR Player, I am preparing to attend a major conference on data and statistics next week in Brussels, with participation of national statistical institutes from European and other countries. Official statisticians who mainly used to do surveys, now fully realize the potential of administrative data – large amounts of information already available in the state’s records, cheaper to obtain than surveys or (horribly expensive!) censuses, often more comprehensive and sometimes almost exhaustive, while also avoiding all types of respondent-induced bias. The registers of schools, hospitals and tax offices are likely to be richer and more accurate than whatever an individual may bother to recall and/or declare about their education, health or income. Social science researchers also demand more and more access to administrative data – especially economists who never really liked surveys, and always mistrusted respondents (I’ll develop this in a future post). Northern European countries pioneered use of these data for official statistics and research, and other governments are now following suit.


Meanwhile, the private sector also discovers a wealth of non-survey data, notably through the Internet and data mined from social networking and other online services – the so-called “big data”. Similarly to administrative data, these are traces of human activity that are recorded by some automated computer system, and do not depend on an individual’s memory, cognitive bias or psychological state. In this sense they can be more accurate than surveys, interviews and questionnaires. Even at the individual level, I can retrace my monthly expenditures more easily and precisely by looking at my credit card records online, than painstakingly trying to recall date, time, amount and place of each transaction. So, from the viewpoint of a researcher, mining large amounts of these data may give a very precise and accurate picture of a human activity, with a level of detail that surveys could never hope to achieve. Combined with the computational capacities of today, which allow handling larger amounts of data than was ever possible in the past, the social and economic sciences have a new tool in their hands that may bring a decisive improvement in their capacity to understand society and advise policy makers.

Particularly interesting is the vision of relational activities provided by big data from social networking services: relationships between people recorded as they access and use the service. When I’m on Twitter, it means that I’m talking to someone. When I’m on Facebook, it means that I have friends (or at least contacts if we don’t want to take the “friendship” metaphor too strictly). For a social networks scholar, this is great to know.

Continue reading ‘Again on data and big data in social research’

I was interviewd by SFR PLAYER (an online magazine published by SFR, a major Telecom provider in France) on the changes induced by the use of big data in my work as a social science researcher. The video interview (in French) is available here. The same issue features an interview with danah boyd and various specialists of open data, data journalism, Internet data.


Interestingly, the video was shot at the École Normale Supérieure Campus Jourdan in Paris, a place that hosts part of Réseau Quetelet, the French national data service for the social sciences and humanities. The Jourdan unit ADISP handles primarily statistical data – data from surveys conducted by INSEE, the French national statistical agency, and administrative data such as those of the ministries of education and labour – for use in the social sciences.

In fact, research in social sciences has always used data as a basic ingredient. Data from official and public-sector statistics have long set the standard, and access to these data is ever more in demand today. European initiatives like the Data without Boundaries project in which I am taking part, aim precisely to bring improvements in this area.

We are now in the midst of a major upgrade today with the availability of big data, data from the Internet, the digital traces of our activities. They have the advantage that they can be retrieved, saved, coded and processed much faster, much more easily and in much larger amounts than more classical records such as registers of students in schools or of patients in hospitals. McKinsey has already pointed to potential economic benefits of big data for business, and research has taken notice too.

Continue reading ‘Data and big data: digital traces of social phenomena to nourish research’

The one-day workshop on “Introduction to Social Network Analysis” that I gave two weeks ago (wow, time flies…) at the University of Greenwich was a great satisfaction! A good audience of about 15 people (not too few, not too many), all very bright and nice. We had interesting and stimulating questions, and it was quite an inspiring event – I take this opportunity to thank all those who attended!

I am going to soon give another such workshop. It will take place on Tuesday, 21 May in the afternoon and on Wednesday, 22 May in the morning at the University of Hamburg, Germany, and it will be one of the many workshops preceding the 2013 Sunbelt conference (for those who aren’t familiar with it, it is the main international venue for experts of social network analysis). It will follow pretty much the same structure as at Greenwich, but based on past experience, I will shorten the theoretical introduction and dedicate more time to network metrics and measures, and their practical calculation and visualisation on the computer (with Gephi). This will make the workshop more interactive, while allowing enough time for participants to become familiar with formal concepts they may never have heard before. The other novelty is that the workshop will be taught jointly with Yasaman Sarabi, a PhD student at Greenwich who specializes in organisational network analysis. Together, we will be better able to support participants and help them with the software.

For those who have a particularly strong interest in social network analysis and cannot be content with just a one-day “taster”, I will also offer an intensive, two-week course on “Doing research with SNA“. It will be part of a Summer School organised at the University of Greenwich on 17 – 25 June 2013, just before the annual conference of the UK Social Networks Association. This course, also taught with Yasaman Sarabi, will review theories and measures, with computer applications (also using Gephi, but also UCINET and Netdraw); in addition, it will offer insight into, and hands-on experience in, research design, organising working groups in which participants set up and conduct a mini-research project, and then present their results. The objective is to help participants identify how they can integrate social network analysis into their own research, and how to reframe their questioning in order to allow for network concepts to play a role. The summer course targets PhD students and junior researchers as a priority, and (like all workshops I give) presupposes no preliminary knowledge of social network analysis, statistics, or computer programming.

More information on the Sunbelt workshop is available here.

More information on the Greenwich summer course is here.

Peru2008_BorrowersI am going to give another one-day workshop on Introduction to Social Network Analysis  in a couple of weeks time -more precisely on Monday, 14th January, at the University of Greenwich, London, as part of a Winter School for researchers and PhD students in social science, management and economics, dedicated to Analytical Software.

The rationale is pretty much the same as usual. I have stressed many times how the recent rise of online social networking services (Facebook, LinkedIn, Twitter etc.) has drawn massive attention to the field of study of social network analysis (SNA). Yet social networks have always existed and are in fact a constant of human experience  – whether in the family, with friends, at school or on the workplace, to name but a few examples. Likewise, SNA already has a respectable history and has been successfully applied to study a wide variety of social contexts.

The workshop is aimed at those who are new to the field, and would like to betterIndia2009_Borrowers understand whether and how they can use it to enhance their own scholarly practice (whether it is research, teaching or consultancy). All social science backgrounds are welcome, and participants are assumed not to have any previous  knowledge of SNA (or statistics or software use, programming etc.). The goal of the workshop is to provide attendees with basic insight into what social network analysis is, and how it can be used in social science research, together with some hands-on experience of how to use network data and how to graphically represent networks, calculate key metrics, and perform some elementary analyses with Gephi, a powerful, though user-friendly, open-source software for visualizing and analyzing networks graphs.

Continue reading ‘A new “Introduction to SNA” short course soon!’


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