Claudio Castellano on Statistical Physics of Social Dynamics
New Hot Paper Commentary, November 2010
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Article: Statistical physics of social dynamics
Authors: Castellano, C;Fortunato,
S;Loreto, V |
Claudio Castellano talks with ScienceWatch.com and answers a few questions about this month's New Hot Papers paper in the field of Physics.
Why do you think your paper is highly
cited?
Because it is essentially the only general review in a very active field, that of application of statistical physics to understanding dynamical processes occurring in social systems. While other more focused reviews have appeared before and afterwards, ours has a broader scope, encompassing several different subfields, such as opinion and cultural dynamics, language origin and competition, crowd dynamics, and others.
We also tried to highlight common trends and shared concepts within a large body of work, and this probably encourages scholars to cite our review even if they are not dealing exactly with the topics discussed in our paper.
Does it describe a new discovery, methodology, or
synthesis of knowledge?
It is a review paper; hence it describes both new discoveries, new methodologies, and a synthesis of knowledge.
Would you summarize the significance of your paper
in layman's terms?
"The pervasive digital fingerprints of virtually all social activities in our modern world call for this truly interdisciplinary endeavour."
In recent years, there has been a rapidly increasing interest for interdisciplinary applications of concepts and methods of statistical physics to social dynamics. The underlying idea, which in some form dates back to founders of social science such as Comte and Quetelet, is that many macroscopic features of social systems are the emergent result of collective "self-organized" phenomena among a large number of individuals. Conceptually this is not far from the step that led, at the end of 19th century, from the study of individual atoms and molecules to the derivation of thermodynamics based on the statistical physics approach.
In our paper we tried to summarize and put into perspective the intense activity that has been recently carried out on some issues like opinion dynamics or language competition.
Let me stress, however, that the review is intended from the point of view of statistical physics, which is the expertise of the authors. The activity in the field has grown very rapidly in the past few years and we felt that a summary of the work done so far was much needed. The review is targeted at statistical physicists and for this reason it is published in a physics journal.
However, as we discuss in the paper, it is clear that this type of research must become more truly interdisciplinary in the future. The goal should be to bridge the gap between the work of statistical physicists and the research agenda of social science scholars, leading to stronger connections and joint teamwork between the two communities.
How did you become involved in this research, and
how would you describe the particular challenges, setbacks, and
successes that you've encountered along the way?
I started to work on this kind of problems approximately 10 years ago. I was at the International Centre for Theoretical Physics in Trieste (Italy) when I came across the book The Complexity of Cooperation by Robert Axelrod, a prominent political scientist at University of Michigan. In this book I found the description of a very simple model aimed at understanding how "cultural dissemination" takes place. This model bears astonishing similarities with models that have been introduced and studied in statistical physics.
The application of methods of statistical physics to the Axelrod model has led immediately to results that have nicely complemented the powerful qualitative insights by Axelrod. More or less at the same time, many other physicists had started to look into the behavior of similar models, either introduced by social scientists or devised by physicists to describe dynamical aspects of social phenomena.
"...there has been a rapidly increasing interest for interdisciplinary applications of concepts and methods of statistical physics to social dynamics."
Over the years, many interesting models have been introduced and studied, and surprising new results have been found. The simultaneous explosion of the research on complex networks has been beneficial in this respect.
The acceptance among physicists of such interdisciplinary activities has increased; still one of the problems faced by people working in this area has to do with the availability of appropriate outlets for publication. More high- and medium-level multidisciplinary journals are definitely needed. By the same token, the recognition of interdisciplinary curricula is still very limited and this is a big challenge for the career perspectives of young people.
Where do you see your research leading in the
future? Do you foresee any social or political implications for your
research?
I think that we are at the beginning of a revolution. The research described in our paper is a small part of an ongoing much bigger trend towards what has been termed as "computational social science," where physicists, computer scientists, social scientists and others will engage together in quantitatively measuring, modeling, and understanding complex collective social phenomena.
The pervasive digital fingerprints of virtually all social activities in
our modern world call for this truly interdisciplinary endeavor. An
improved understanding of how the social behavior of individuals leads to
large-scale emergent phenomena will be not only interesting per se, but it
will also have a strong impact on societal issues of huge relevance, such
as the optimization of the performance of real and digital transportation
networks, the devising of better social policies, and the prediction of the
occurrence of global instabilities.
Dr. Claudio Castellano
Istituto dei Sistemi Complessi (ISC-CNR) UOS Sapienza and Dipartimento di
Fisica "Sapienza" Universita' di Roma
Roma, Italy
KEYWORDS: SMALL-WORLD NETWORKS; SZNAJD SOCIOPHYSICS MODEL; SELF-PROPELLED PARTICLES; OPINION FORMATION MODEL; MONTE-CARLO-SIMULATION; SCALE-FREE NETWORKS; EVOLUTIONARY LANGUAGE GAME; SIZE STOCHASTIC RESONANCE; BARABASI-ALBERT NETWORKS; CONTRARIAN-LIKE BEHAVIOR.