Flaminio Squazzoni is an assistant professor of economic sociology at the University of Brescia, where he leads the the GECS-Research Group on Experimental and Computational Sociology. He is the President of the European Social Simulation Association (Sept 2012/Sept 2014) and advisory editor of the Wiley Series in Computational and Quantitative Social Science.
His fields of research are agent-based computational sociology, the sociology of markets and peer review. In particular, he is interested to investigate the relevance of social norms and institutions for socio-economic systems’ behaviour by integrating experimental and agent-based computational research.
Statistics Views talks to Professor Squazzoni about his career and the Wiley Series in Computational and Quantitative Social Science.
1. As one of the Series Editors on Computational and Quantitative Social Science (CQSS), when and how did you first become involved with the Series?
I was contacted by Heather Kay at Wiley to discuss this new series some years ago. It seemed to me a good idea, as I believed that a series on quantitative and computational research in social sciences was absolutely needed. So, I reacted enthusiastically since the beginning.
2. Please could you tell us about your educational background and when and how you first become aware of statistics as a discipline?
My background is more in the humanities, having graduated in History. So, statistics was not part of my expertise. Then, I started a PhD in Economic Sociology. During the first year, there was intense training, which also focused on quantitative methods. With a department senior involved in the PhD faculty, I started to contemplate doing a research using agent-based modelling techniques. So, this increased my interest in quantitative methods and tool.
3. What makes this Wiley series different from other book series in the field?
There is no similar example among other publishers. The outstanding Princeton Book Series in Complexity is more addressed to agent-based modelling and is less social science oriented. The same for the Springer Book Series on Complexity. This series is relatively unique in strengthening the quantitative/computational trait-d’-union in looking at social phenomena.
4. Who should be reading the Series and why?
Any social scientist who believes that social sciences are not so different than other sciences and so must adopt serious standards of research.
5. What do you enjoy most about being a Series Editor?
Having the chance of approaching young, talented scholars and suggesting them to write a proposal; seeing good books coming out; reading good proposals in diverse fields.
6. What are your main priorities/objectives for the Series in the year ahead?
Encouraging new scholars to be published and trying also to attract big names.
When I teach experimental sociology, a great problem is sample selection and bias and problems of external validity. This is the same in agent-based modelling. So, standard practices of statistics can be used to discuss these criticalities. The same is for simulation results’ validation. It’s important that computational social science research develops better calibration and validations standards. Statistics, econometrics can help.
7. You have also written a book with Wiley, Agent-Based Computational Sociology. What is it about this area that fascinates you?
The idea of looking at social sciences as a field where common practices and modelling attitudes can develop. Seeing that we can make sociology a more collective and robust endeavour by sharing model findings, replication, extension, which are difficult without modelling.
8. You are currently a professor of economic sociology at the University of Brescia. How did your teaching and research motivate and influence each other? Did you get research ideas from statistics and incorporate them into your teaching?
When I teach experimental sociology, a great problem is sample selection and bias and problems of external validity. This is the same in agent-based modelling. So, standard practices of statistics can be used to discuss these criticalities. The same is for simulation results’ validation. It’s important that computational social science research develops better calibration and validations standards. Statistics, econometrics can help.
9. What is the best academic book that you have ever read?
That’s a hard question. Probably, Micromotives and Macrobehaviour by Thomas Schelling. Or The New Alliance by Prigogine and Stenger.
10. Do you think over the years too much research has focused on less important areas of social sciences and statistics? Should the gap between research and applications get reduced? How so and by whom?
I believe that an area of underdevelopment where progress must be made is policy. I saw some recent progress due to the shock of the global crisis that has called for better social science. Another one of course is Big Data, which calls for new developments also in statistics.
11. If you had not got involved in the field of economic sociology, what do you think you would have done? (Is there another field that you could have seen yourself making an impact on?)
I don’t really know. In any case, I am involved in trans-disciplinary projects and I have always collaborated with economists, econometricians, behavioural scientists and computer scientists. So, I am not a sort of excessively specialized and disciplinary self-referential scientist. Sometime, it’s even hard to believe to be ONLY a sociologist. If I would have another trial, I would probably be what today is called a “behavioural scientist”. It’s great to remember that this label was rarely mentioned when I started my career at the end of the 1990s!
Copyright: Image appears courtesy of Professor Squazzoni