Online Coordination: Methods and Comparative Case Studies of Coordinated Groups across Four Events in the United States

Abstract

Coordinated groups of user accounts working together in online social media can be used to manipulate the online discourse and thus is an important area of study. In this study, we work towards a general theory of coordination. There are many ways to coordinate groups online: semantic, social, referral and many more. Each represents a coordination dimension, where the more dimensions of coordination are present for one event, the stronger the coordination present. We build on existing approaches that detect coordinated groups by identifying high levels of synchronized actions within a specified time window. A key concern with this approach is the selection of the time window. We propose a method that selects the optimal window size to accurately capture local coordination while avoiding the capture of coincidental synchronicity. With this enhanced method of coordination detection, we perform a comparative study across four events: US Elections Primaries 2020, Reopen America 2020, Capitol Riots 2021 and COVID Vaccine Release 2021. Herein, we explore the following three dimensions of coordination for each event - semantic, referral and social coordination - and perform group and user analysis within and among the events. This allows us to expose different user coordination behavior patterns and identify narratives and user support themes, hence estimating the degree and theme of coordination.