Statistical physics of social dynamics
By Claudio Castellano, Santo Fortunato, Vittorio Loreto. 2007
3,849 citations recorded by the source corpus.
Statistical physics has proven to be a fruitful framework to describe phenomena outside the realm of traditional physics. Recent years have witnessed an attempt by physicists to study collective phenomena emerging from the interactions of individuals as elementary units in social structures. A wide list of topics are reviewed ranging from opinion and cultural and language dynamics to crowd behavior, hierarchy formation, human dynamics, and social spreading. The connections between these problems and other, more traditional, topics of statistical physics are highlighted. Comparison of model results with empirical data from social systems are also emphasized.
Subfields: Sociology and Political Science, Statistical and Nonlinear Physics
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Sociology and Political Science
- Matjaz Perc
- Attila Szolnoki
- Filippo Menczer
- Kristina Lerman
- Alessandro Flammini
- Zhen Wang
- Stefano Boccaletti
- Jillian J. Jordan
In Statistical and Nonlinear Physics
- Matjaz Perc
- Mark Newman
- Maizar Raissi
- G. Em Karniadakis
- Marc Barthelemy
- Paris Perdikaris
- M. A. Porter
- Santo Fortunato
Citations in the corpus
- Multistep Neural Networks for Data-driven Discovery of Nonlinear Dynamical Systems (2018, background): “In this setting, one may be only able to postulate crude and potentially overly simplified models based on a given a set of empirical observations (see e.g., models for tumor growth [2], social dynamics [3], and the stock market [4]).”
- Quantifying Long-Term Scientific Impact (2013, background): “[17] C.”
- Crises and Collective Socio-Economic Phenomena: Simple Models and Challenges (2012, neutral): “Zhang, Minority Games, Oxford University Press, (2005) [31] C.”
- Social Influence and the Collective Dynamics of Opinion Formation (2013, methodology): “Scaling up from individual to collective behavior was achieved by means of computer simulations in line with existing approaches in the field of self-organization and complex systems [2,9,19].”
- Coevolutionary games - A mini review (2009, neutral): “…also change or evolve in the course of time (Caldarelli et al., 1998; Pfeiff r et al., 2005; Holme and Ghostal, 2006; Gross and Blasius, 2008; Castellano et al., 2009); in particularly so, since the term ‘coevolution’ has in the past been used quite frequently and for rather different…”
- The statistical physics of cities (2019, background): “The possibility of a quantitative analysis of social aggregate states is opened by the availability of large amounts of data about techno-social systems [8] (see for example the review about statistical physics of social dynamics [9]).”
- Recommender Systems (2012, background): “Physicists, with their long experience with data-driven research, have joined this trend and contributed to many fields such as finance [3, 4], network theory [5, 6, 7, 8, 9] and social dynamics [10] which are outside their traditional realm.”