Investigating Visual Content Shared over Twitter during the 2019 EU Parliamentary Election Campaign

Open Access Journal | ISSN: 2183-2439

Article | Open Access

Investigating Visual Content Shared over Twitter during the 2019 EU Parliamentary Election Campaign


  • Nahema Marchal Oxford Internet Institute, University of Oxford, UK
  • Lisa-Maria Neudert Oxford Internet Institute, University of Oxford, UK
  • Bence Kollanyi Doctoral School of Sociology, Corvinus University of Budapest, Hungary
  • Philip N. Howard Oxford Internet Institute, University of Oxford, UK


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Abstract:  Political communication increasingly takes on visual forms. Yet, despite their ubiquity in everyday communication and digital campaigning, the use of these visuals remains critically understudied. In this article, we investigate the formats and modes of visual content deployed by Twitter users over a two-week period leading up to the 2019 EU Parliamentary elections and across two publics: those discussing the election at large and those discussing the more contentious issue of EU membership. Conducting a multilingual, cross-comparative content and thematic analysis of a sample of 1,097 images, we find that: (1) Visuals originating from traditional political actors prevailed among both Twitter discourses; (2) users shared substantial amounts of anti-EU, populist and, to a lesser extent, extremist images, though this content remained largely disjointed from the mainstream public debate; and (3) political humor emerged as a vector for anti-establishment and Eurosceptic themes, especially in discussions critical of the European project. We discuss the implications of our findings for the study of visual political communication and social media manipulation.

Keywords:  elections; European politics; populism; social media; visual communication

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DOI: https://doi.org/10.17645/mac.v9i1.3421


© Nahema Marchal, Lisa-Maria Neudert, Bence Kollanyi, Philip N. Howard. This is an open access article distributed under the terms of the Creative Commons Attribution 4.0 license (http://creativecommons.org/licenses/by/4.0), which permits any use, distribution, and reproduction of the work without further permission provided the original author(s) and source are credited.