Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/330604 
Year of Publication: 
2024
Citation: 
[Journal:] Information Systems Frontiers [ISSN:] 1572-9419 [Volume:] 27 [Issue:] 4 [Publisher:] Springer US [Place:] New York, NY [Year:] 2024 [Pages:] 1425-1443
Publisher: 
Springer US, New York, NY
Abstract: 
As per agenda-setting theory, political agenda is concerned with the government's agenda, including politicians and political parties. Political actors utilize various channels to set their political agenda, including social media platforms such as Twitter (now X ). Political agenda-setting can be influenced by anonymous user-generated content following the Bright Internet. This is why speech acts, experts, users with affiliations and parties through annotated Tweets were analyzed in this study. In doing so, the agenda formation during the 2019 European Parliament Election in Germany based on the agenda-setting theory as our theoretical framework, was analyzed. A prediction model was trained to predict users' voting tendencies based on three feature categories: social, network, and text. By combining features from all categories logistical regression leads to the best predictions matching the election results. The contribution to theory is an approach to identify agenda formation based on our novel variables. For practice, a novel approach is presented to forecast the winner of events.
Subjects: 
2019 European parliament election
Social media analytics
User’s voting prediction
Agenda-setting theory
Political agenda
Persistent Identifier of the first edition: 
Creative Commons License: 
cc-by Logo
Document Type: 
Article
Document Version: 
Published Version

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