REVEALING COORDINATED IMAGE-SHARING IN SOCIAL MEDIA: A CASE STUDY OF PRO-RUSSIAN INFLUENCE CAMPAIGNS

Abstract

Coordinated online disinformation campaigns are by nature difficult to detect. In response, communication scholars have developed a range of methods and analytical frameworks to discover and analyse disinformation campaigns. The use of social network analysis (SNA) to find and map coordinated behavioural patterns has become increasingly popular and demonstrated effective results. However, these methods are designed for text and behavioural but miss an important aspect of disinformation campaigns: coordinated image-sharing. This paper examine this gap by analysing a large-scale dataset of tweets using advanced SNA to map coordinated retweeting behaviour and coordinated image-sharing. We show that coordinated image-sharing is both more widespread and different in structure to other forms of coordination. This is important because it highlights a major gap in research, where computational methods are not suited to detecting and analysing the scale and scope of visual disinformation on platforms like Twitter. To address this, we suggest new methods to complement existing approaches, using machine learning to detect image similarity. The paper concludes with a reflection of limitations and suggestions for the next steps.