Pics or It Didn’t Happen - Visual Communication Strategies of EU Institutions on Social Media

The European Union is repeatedly found to suffer from a participation deficit, rooted in the fact that it is perceived as far away from people’s lives, giving them little room for directly experiencing European politics. Given this remoteness, media coverage was often the only way for citizens to learn about the EU. Mass media coverage was, however, long characterised by low visibility of the topic and then superseded by more extensive, but more negative coverage during a decade of EU crises. Social media were, therefore, welcomed as a direct way to communicate to European publics, circumventing the gatekeeping function of the mass media. Social media affordances shape visibility and persistence of such information sharing as well as direct engagement of users in terms of liking, sharing, or communicating in the comment section. Moreover, many of these social media follow a visual logic, which has been found to increase engagement with political communication contents distinctly, as images are more likely to attract attention and present information on a holistic-associative basis. Taking these considerations as a point of departure, our study is the first to undertake a multimodal analysis of communication by different EU institutions, comparing social media platforms (Facebook and Instagram) regarding (visual and textual) contents as well as user engagement with these contents over the last 10 years. Relying on a mixed methods design, (1) we employ an image-type content analysis, which combines quantitative and qualitative features of visual analysis. In a first step, a sub-sample of posts is inductively analysed to identify recurring image types, which are subsequently used as categories in a manual quantitative visual content analysis. This content analysis further examines variables like the captions of posts, text elements embedded in images as well as visual features as extracted from the pictures. Building on the results, (2) we then implement a machine learning approach to scale up the analysis, eventually allowing us to analyse the whole dataset of 46,467 posts, including more than 20,000 pictures, to identify patterns and dynamics in the social media communication of the EU. Our study contributes to a growing body of literature focusing on the challenges of visual content analysis. We also enhance the still underdeveloped debate about the distinct affordances of and user interaction on different social media platforms. Finally, our analysis adds to the ongoing discussion about the EU’s democratic deficit, also informing EU public relations practitioners regarding viable strategies to increase user interaction with their contents.