Contextualizing Representations of Violence in #Blacklivesmatter Coverage with Inductive Computational Content Analysis

Abstract

ABSTRACT News coverage of social movements traditionally adheres to the protest paradigm, which focuses on violent and confrontational tactics instigated by activists. Recent work has called for a reevaluation of this theory through the lens of partisan media bias. We demonstrate how partisan media bias systematically shapes coverage of the summer 2020 Black Lives Matter protests that occurred in the aftermath of the police murder of George Floyd. Using an inductive computational content analysis, we surface words and phrases that best predict whether an article was published in a left-, center-, or right-leaning outlet. We then perform a qualitative close reading of those terms in context to determine how partisan media bias shapes depictions of the same events: namely, in representations of protestors and violence. Right-leaning media depict protestors as violent rioters, looters, and antifa members committing property damage, whereas center- and left-leaning media emphasize the peaceful nature of the protests motivated by the police killing of Floyd and systematic racism. We consider the implications of these findings on broader public opinion within media ecosystems.