Detecting Pivotal Points in Social Conflicts via Topic Modeling of Twitter Content

Abstract

The linkages between intensity and topicality of online discussions, on one hand, and those of offline on-street political activity, on the other hand, have recently become a subject of studies around the world. But the results of quantitative assessment of causal relations between onsite and online activities of citizens are contradictory. In our research, we use conflicts with violent trig-gers and the subsequent lines of events that include street rallies, political manifestations, and/or peaceful mourning, as well as public political talk, to trace the pivotal points in the conflict via measuring Twitter content. We show that in some cases Granger test does not work well, like in the case of Cologne mass harassment, for detecting the causality between online and onsite activities. In order to suggest a way to qualitatively assess the linkages between online and offline activities of users, we deploy topic modeling and further qualitative assessment of the changes in the topicality to link the topic saliency to the time of offline events. We detect several periods with varying topicality and link them to what was going on in the offline conflict.