Identifying Key Players and Themes in Michigan Protests Through Social Network Analysis

In the early period of the COVID-19 pandemic, Michigan became a focal point of socio-political unrest, which also led to a parallel surge in Twitter activity. This study applies social network analysis (SNA) to 15,681 unique tweets related to Michigan protests to unravel the complex user interactions and conversational themes. SNA explores community structures, key figures, and prevailing narratives; connecting the physical protests to their online counterparts. An analysis of user interactions reveals many distinct, sparsely connected communities, accentuated by pivotal roles of political figures like Governor Whitmer and former President Trump. The influence of alternative media sources in driving and polarizing these conversations is also evident. An analysis of hashtag co-occurrences also reveals many distinct groups that probably share smaller subsets of overlapping interests within the broad realm of issues germane to the protests. Taken together, this suggests that users coalesce into polarized echo chambers, each dedicated to a few coherent issues; and concerns of one may be inherently at odds with others. The encouraging aspect, however, is that both user and hash tag networks carry the capacity for communication and exchange of ideas across these echo chambers. This capacity can be exploited to break down the polarization and cultivate empathy among disparate groups through exchange of perspectives. These findings can thus be leveraged to develop effective communication and sharing strategies, especially during socially turbulent situations.