Uncovering Social Media Reaction Pattern to Protest Events: A Spatiotemporal Dynamics Perspective of Ferguson Unrest

  • Jiaying He
  • Lingzi Hong
  • Vanessa Frias-Martinez
  • Paul Torrens
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9471)


Social platforms like Twitter play an important role in people’s participation in social events. Utilizing big social media data to uncover people’s reaction to social protests can shed lights on understanding the event progress and the attitudes of normal people. In this study, we aim to explore the use of Twitter during protests using Ferguson unrest as an example from multiple perspectives of space, time and content. We conduct an in-depth analysis to unpack the social media response and event dynamics from a spatiotemporal perspective and to evaluate the social media reaction through the integration of spatiotemporal tweeting behavior and tweet text. We propose to answer the following research questions. (1) What is the general spatiotemporal tweeting patterns across the US? (2) What is the spatiotemporal tweeting patterns in local St. Louis? (3) What are the reaction patterns in different US urban areas in space, time and content?


Social Medium Social Movement Normal User Reaction Pattern Media Outlet 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  • Jiaying He
    • 1
  • Lingzi Hong
    • 2
  • Vanessa Frias-Martinez
    • 2
  • Paul Torrens
    • 1
  1. 1.Department of Geographical SciencesUniversity of MarylandCollege ParkUSA
  2. 2.School of Information StudiesUniversity of MarylandCollege ParkUSA

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