Meier, Florian and Bazo, Alexander and Elsweiler, David (2022) Using Social Media Data to Analyse Issue Engagement During the 2017 German Federal Election. ACM TRANSACTIONS ON INTERNET TECHNOLOGY, 22 (1): 25. ISSN 1533-5399, 1557-6051
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A fundamental tenet of democracy is that political parties present policy alternatives, such that the public can participate in the decision-making process. Parties, however, strategically control public discussion by emphasising topics that they believe will highlight their strengths in voters' minds. Political strategy has been studied for decades, mostly by manually annotating and analysing party statements, press coverage, or TV ads. Here we build on recent work in the areas of computational social science and eDemocracy, which studied these concepts computationally with social media. We operationalize issue engagement and related political science theories to measure and quantify politicians' communication behavior using more than 366k Tweets posted by over 1,000 prominent German politicians in the 2017 election year. To this end, we first identify issues in posted Tweets by utilising a hashtag-based approach well known in the literature. This method allows several prominent issues featuring in the political debate on Twitter that year to be identified. We show that different political parties engage to a larger or lesser extent with these issues. The findings reveal differing social media strategies by parties located at different sides of the political left-right scale, in terms of which issues they engage with, how confrontational they are and how their strategies evolve in the lead-up to the election. Whereas previous work has analysed the general public's use of Twitter or politicians' communication in terms of cross-party polarisation, this is the first study of political science theories, relating to issue engagement, using politicians' social media data.
| Item Type: | Article |
|---|---|
| Uncontrolled Keywords: | POLITICAL COMMUNICATION; CAMPAIGNS; CONVERGENCE; CANDIDATES; OWNERSHIP; TWITTER; COMPETITION; AVOIDANCE; MESSAGES; FACEBOOK; Computational social science; eDemocracy; issue engagement; twitter; political communication |
| Subjects: | 000 Computer science, information & general works > 000 Generalities, Science 000 Computer science, information & general works > 020 Library & information sciences |
| Divisions: | Languages and Literatures > Institut für Information und Medien, Sprache und Kultur (I:IMSK) > Lehrstuhl für Informationswissenschaft (Prof. Dr. Udo Kruschwitz) Informatics and Data Science > Department Human-Centered Computing > Lehrstuhl für Informationswissenschaft (Prof. Dr. Udo Kruschwitz) |
| Depositing User: | Dr. Gernot Deinzer |
| Date Deposited: | 15 Feb 2024 13:19 |
| Last Modified: | 15 Feb 2024 13:19 |
| URI: | https://pred.uni-regensburg.de/id/eprint/57683 |
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