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Forecasting Social Unrest Using Activity Cascades.

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Researchers developed a model to forecast civil unrest using Twitter activity cascades. This approach predicts real-world protests by identifying online precursors, demonstrating effectiveness in Latin America.

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Area of Science:

  • Social Sciences
  • Computational Social Science
  • Network Science

Background:

  • Social unrest and civilian mobilization are prevalent globally, necessitating predictive tools for social scientists and policymakers.
  • Media platforms like Twitter offer potential indicators for forecasting civil unrest and protest events.
  • Understanding the dynamics of online activity is crucial for anticipating real-world social movements.

Purpose of the Study:

  • To develop and validate an event forecasting model for predicting protests using Twitter activity cascades.
  • To investigate the relationship between online activity cascades and ground-level protest occurrences.
  • To apply spectral properties for characterizing large cascades and forecasting events.

Main Methods:

  • Utilized a novel event forecasting model based on Twitter activity cascades, drawing from Gonzalez-Bailon et al. (2011).
  • Analyzed spectral properties to theoretically characterize large cascades.
  • Employed detected cascade properties to forecast protest events in Brazil, Mexico, and Venezuela.

Main Results:

  • The proposed model successfully predicted protest events in three Latin American countries.
  • Experimental results, including the June 2013 Brazil protests, validated the model's effectiveness.
  • Demonstrated that detected activity cascades on Twitter can serve as precursors to real-world protests.

Conclusions:

  • The activity cascade model provides a viable method for forecasting civil unrest and protests.
  • Online social media activity, specifically Twitter cascades, can be a significant indicator of impending social movements.
  • This approach offers valuable insights for social scientists and policymakers seeking to anticipate and understand social unrest.