Predicting Opinion Leaders in Twitter Activism Networks: The Case of the Wisconsin Recall Election

This study employs content and network analysis techniques to explore the predictors of opinion leadership in a political activist network on Twitter. The results demonstrate the feasibility of using user-generated content to measure user characteristics. The characteristics relevant to the study were analyzed to predict user performance in the network, tracking subjects like activity, information output, and circulation. According to the results, Twitter users with higher connectivity and issue involvement are better at influencing information flow on Twitter, creating a constant impression of engagement. User connectivity was measured by betweenness centrality, and issue involvement was measured by a user’s geographic proximity to a given event and the contribution of engaging tweets. In addition, the results show that tweets by organizations had greater influence than those by individual users.

This study will be of interest to researchers and practitioners in the field of PVE, as its findings relate to material that could be applied to electoral networks as well as extremist or far right-wing recruitment, propaganda or command and control hubs. Twitter’s increasingly prevalent role as a tool of exposure and indoctrination by extremist organizations ties neatly into the regionalism of this topic.

Full article is available here >>