Comparing the #StopTheSteal Movement across Multiple Platforms: Differentiating Discourse on Facebook, Twitter, and Parler

Abstract

Given that political groups are dispersed across platforms, resulting in different discourses, there is a need for more studies comparing communication across platforms. In this study, we compared posts about #StopTheSteal from three social media platforms after the 2020 US Presidential election and preceding the January 6 Capitol Riot. To do so, we utilized Snow and Benford’s typology of social movement frames—diagnostic, prognostic, and motivational frames—in the context of far-right movements and an additional frame device: violence cues. This study focused on the following three social media platforms: Facebook, Twitter, and Parler. We built three corpora of social media data: 26,093 Facebook posts, 248,643 tweets, and 400,600 Parler posts. Using Bidirectional Encoder Representations from Transformers (BERT) classifiers, dictionary methods, and qualitative text analysis, we find that the use of these frames varies by platform, with users on the alt-tech platform Parler using violence cues such as “smash” and “combat,” suggesting a greater call to action relative to the mainstream platforms.