An actor-based approach to understanding radical right viral tweets in the UK

Abstract

Radical right actors routinely use social media to spread highly divisive, disruptive, and anti-democratic messages. Assessing and countering such content is crucial for ensuring that online spaces can be open, accessible, and constructive. However, previous work has paid little attention to understanding factors associated with radical right content that goes viral. We investigate this issue with a new dataset (the ‘ROT’ dataset) which provides insight into the content, engagement, and followership of a set of 35 radical right actors who are active in the UK. ROT contains over 50,000 original entries and over 40 million retweets, quotes, replies and mentions, as well as detailed information about followership. We use a multilevel model to assess engagement with tweets and show the importance of both actor- and content-level factors, including the number of followers each actor has, the toxicity of their content, the presence of media and explicit requests for retweets. We argue that it is crucial to account for role of actors in radical right viral tweets, and therefore, moderation efforts should be taken not only on a post-to-post level but also on an account level.