© 2015

Social Phenomena

From Data Analysis to Models

  • Bruno Gonçalves
  • Nicola Perra

Part of the Computational Social Sciences book series (CSS)

Table of contents

  1. Front Matter
    Pages i-xii
  2. Bruno Gonçalves, Nicola Perra
    Pages 1-12
  3. Social Behavior Under Normal Conditions

    1. Front Matter
      Pages 13-13
    2. Jameson L. Toole, Yves-Alexandre de Montjoye, Marta C. González, Alex (Sandy) Pentland
      Pages 15-35
    3. Alain Barrat, Ciro Cattuto
      Pages 37-57
    4. Nicola Perra, Bruno Gonçalves
      Pages 59-83
    5. Tobias Preis, Helen Susannah Moat
      Pages 85-97
    6. Lilian Weng, Filippo Menczer, Alessandro Flammini
      Pages 99-116
    7. Filippo Radicchi, Claudio Castellano
      Pages 135-151
  4. Social Behavior Under Stress

    1. Front Matter
      Pages 153-153
    2. Piero Poletti, Marco Ajelli, Stefano Merler
      Pages 155-175
    3. Emilio Ferrara, Salvatore Catanese, Giacomo Fiumara
      Pages 177-207
    4. Neil F. Johnson, Elvira Maria Restrepo, Daniela E. Johnson
      Pages 209-233
  5. Back Matter
    Pages 251-260

About this book


This book focuses on the new possibilities and approaches to social modeling currently being made possible by an unprecedented variety of datasets generated by our interactions with modern technologies. This area has witnessed a veritable explosion of activity over the last few years, yielding many interesting and useful results. Our aim is to provide an overview of the state of the art in this area of research, merging an extremely heterogeneous array of datasets and models. Social Phenomena: From Data Analysis to Models is divided into two parts. Part I deals with modeling social behavior under normal conditions: How we live, travel, collaborate and interact with each other in our daily lives. Part II deals with societal behavior under exceptional conditions: Protests, armed insurgencies, terrorist attacks, and reactions to infectious diseases. This book offers an overview of one of the most fertile emerging fields bringing together practitioners from scientific communities as diverse as social sciences, physics and computer science. We hope to not only provide an unifying framework to understand and characterize social phenomena, but also to help foster the dialogue between researchers working on similar problems from different fields and perspectives.


Computational Tools for Criminal Behavior Data-driven Social Sciences Human Behavior in Financial Markets Human Dynamics Modeling And Understanding of Social Events Modeling Infectious Diseases Modeling Social Contagion Modeling Terroristic Escalations Online Social Networks Proxy Data for Social and Behavioral Analysis Social Contagion and Information Diffusion Social Network Analysis Tools for Criminal Behavior

Editors and affiliations

  • Bruno Gonçalves
    • 1
  • Nicola Perra
    • 2
  1. 1.Centre de Physique ThéoriqueAix-Marseille Université Campus de Luminy, Case 907MarseilleFrance
  2. 2.MoBS LabNortheastern UniversityBostonUSA

Bibliographic information


“As a collection of state-of-the-art summaries and several interesting applications, it could easily form the foundation of multidisciplinary conversations on the future of big data and modeling and simulation to advance understanding of social phenomena. Social Phenomena would serve as a solid starting point for those researchers interested in delving into the increasingly large, available datasets to enhance their models.” (Erika Frydenlund, JASSS The Journal of Artificial Societies and Social Simulation, Vol. 19 (2), March, 2016)

“This book is essentially a reference book on data analysis and models. It does a superb job in this domain.” (M. M. Tanik, Computing Reviews, January, 2016)