TY - JOUR
T1 - Communicating Europe
T2 - A computational analysis of the evolution of the European Commission’s communication on Twitter
AU - Rocca, Roberta
AU - Lawall, Katharina
AU - Tsakiris, Manos
AU - Cram, Laura
PY - 2024/4/17
Y1 - 2024/4/17
N2 - Social media is an important means of communication for political agencies, which makes it possible to engage with large sectors of the public. For institutions which are not directly elected by voters, such as the European Commission (EC), social media can be a strategic tool for increasing perceived legitimacy and citizen engagement, especially in contexts of high politicization. In this paper, we use natural language processing techniques to provide a comprehensive overview of how EC communication on Twitter has evolved between 2010 and 2022, with respect to both its topics and its style. Our analyses show that, over time, the focus of EC communication has shifted substantially from economy-, finance- and governance-related topics, towards social policy, digital and environmental policy, and identity. These changes have progressively differentiated the EC’s profile from that of other institutions (especially more technocratic ones) and contributed to better alignment with engagement patterns of its social media audience. In addition, EC communication has become less neutral (in favor of more positive sentiment), simpler, and more readable, all features which are associated with more accessible and engaging messaging. Yet, while the EC currently scores better than most other reference agencies on several descriptors of accessibility, its style is still lexically more complex, less concrete and less action-oriented than that of other institutions. Alongside providing novel insights on how the EC’s online communication and projected political identity have changed over time, this study lays the foundations for future experimental and hypothesis-driven work combining social media data with external data sources.
AB - Social media is an important means of communication for political agencies, which makes it possible to engage with large sectors of the public. For institutions which are not directly elected by voters, such as the European Commission (EC), social media can be a strategic tool for increasing perceived legitimacy and citizen engagement, especially in contexts of high politicization. In this paper, we use natural language processing techniques to provide a comprehensive overview of how EC communication on Twitter has evolved between 2010 and 2022, with respect to both its topics and its style. Our analyses show that, over time, the focus of EC communication has shifted substantially from economy-, finance- and governance-related topics, towards social policy, digital and environmental policy, and identity. These changes have progressively differentiated the EC’s profile from that of other institutions (especially more technocratic ones) and contributed to better alignment with engagement patterns of its social media audience. In addition, EC communication has become less neutral (in favor of more positive sentiment), simpler, and more readable, all features which are associated with more accessible and engaging messaging. Yet, while the EC currently scores better than most other reference agencies on several descriptors of accessibility, its style is still lexically more complex, less concrete and less action-oriented than that of other institutions. Alongside providing novel insights on how the EC’s online communication and projected political identity have changed over time, this study lays the foundations for future experimental and hypothesis-driven work combining social media data with external data sources.
KW - European Commission
KW - natural language processing
KW - political communication
KW - politicization
KW - Twitter
UR - https://github.com/rbroc/eucomm-twitter
UR - http://www.scopus.com/inward/record.url?scp=85190527569&partnerID=8YFLogxK
U2 - 10.1007/s42001-024-00271-w
DO - 10.1007/s42001-024-00271-w
M3 - Article
AN - SCOPUS:85190527569
SN - 2432-2717
SP - 1
EP - 52
JO - Journal of Computational Social Science
JF - Journal of Computational Social Science
ER -