Rumoring During Extreme Events: A Case Study of Deepwater Horizon 2010


Social scientists have proposed many different factors thought to influence rumoring behavior. Classical rumor theory points to the perceived importance, the level of uncertainty or ambiguity, and the potential to impact decision making as influential in determining the extent of rumoring. In this work, we test some of these proposed rumor determinants in the context of the the 2010 Deepwater Horizon oil spill, using data on communication dynamics from the popular microblogging service Twitter. Using a latent factor model, we measure rates of hazard-related conversation by exploiting joint variation in multiple conversation streams. Time series analysis of the resulting rates suggests that media coverage of the event is a major driver of rumoring behavior, supporting importance/saliency theories and disconfirming theories of information substitution for this event. Relevance of the event to decision making behavior also turns out to be an influential predictor in this case. Since information diffusion via serial transmission is a fundamental process by which rumors spread, we compare rates of serial transmission between control and hazard-related communication. Twitter posts are much more likely to be retweeted when they contain hazard-related keywords (versus control words). Implications of these findings for disaster response are discussed.

Proceedings of the ACM Web Science 2012 Conference