Modeling and Forecasting Social Movements

Call For Papers

Journal of Defense Modeling and Simulation (JDMS)

Special Issue: Modeling and Forecasting Social Movements


A range of advanced modeling techniques holds the promise of more effectively predicting the emergence and prospects of social movements and other forms of social contention. Given the rich and dynamically changing context of modern communications, however, significant challenges remain. This call invites contributions addressing the research question of how social change and behavior can be analyzed, modeled and predicted in a provable repeatable way.

Public opinion and societal behavior are formed in the space of mediated information and communication. We live in a world of diversified and recombining messages digested by both distant and co-located minds with increasingly autonomous sources of information. Governments, corporations, media organizations, individuals and communities produce data that represents a stream of consciousness of society, albeit a stream with many competing voices, agendas, and noise. Computational access to this data opens up unprecedented opportunities to read the collective mind and offers the possibility of discovering emergent societal trends while they are still being hatched by small groups of individuals. This data could allow researchers in predictive modeling and analytics to understand why some new ideas change the lives of entire populations, while others never get off the ground.

Embedded in this stream of fact and fiction are the opinions and activities that will change societies and make news. Social change is, hence, cause and effect in a complex dependency between technological, natural, social and cultural drivers. They might account for factors like repression, protests and revolutions, governmental aid, support for countries to help build security, and Internet and mobile phone usage, influencing both radical as well as subtle, long-term change.

Methods for analysis may be based on corpora of digital traces of human activity, in particular the Web, Blogs, online forums, social networking sites, or e-mail archives. Sources could also be outside of social media; they might be open-source but not necessarily online, or semi-public, such as material from court hearings, governmental panels, think tanks, expert meetings including research conferences, etc.. Datasets can be very large, such as twitter archives, but they might also be triangulated from small or very sparse datasets.

Forecast models track existing social groups, and infer the formation of new groups, in a manner that might be generalizable across cultures. Methods may include continuous, automated analysis of publicly available data in order to detect and anticipate significant societal events, combining topic content with valence, such as emotions, religions, or beliefs, in order to determine underlying psychological and societal states.

We invite researchers in the field to submit their latest, unpublished work in:

  • Deriving social relations and information flow patterns from topic content over time, identifying social movements
  • Agent-based models of social change and unrest
  • Social media monitoring
  • Application of mathematical models of social theory
  • Predictive Analytics, including, for instance, methods based on neural networks, evolutionary algorithms, and machine learning
  • Analytic & statistical techniques such as Granger causality, simplex prediction, Support Vector Machines, and Bayesian inference methods
  • Analysis of valence, e.g. sentiments, opinions, beliefs, religion
  • Group identity extraction and reputation analysis
  • Other methodologies that fit the scope of this call

Due Dates

Full Papers Due February 28, 2013
Reviews returned to authors June 30, 2013
Revised papers due July 30, 2013
Notification of Acceptance Sept. 30, 2013
Submission of Final (revised) Paper Oct. 30, 2012
Publication Expected Spring/Summer 2014

Final Paper Submissions

Each final submission must be prepared based on the JDMS journal requirements (see the Author Guidelines for JDMS page).

Manuscripts should be prepared and submitted online at the SCS Manuscript Management System. Please note in your online cover letter that your submission is intended for the "Special Issue: Modeling and Forecasting Social Movements."


  • Peter A. Gloor
    MIT Center for Collective Intelligence
  • Jana Diesner
    iSchool, University of Illinois at Urbana Champaign
  • Kai Fischbach
    University of Bamberg
  • Joe Parry
    Cambridge Intelligence
  • David L. Sallach
    Argonne National Laboratory and the University of Chicago