Agenda Formation and Prediction of Voting Tendencies for European Parliament Election using Textual, Social and Network Features

Gautam Kishore Shahi (), Ali Sercan Basyurt, Stefan Stieglitz and Christoph Neuberger
Additional contact information
Gautam Kishore Shahi: University of Duisburg-Essen
Ali Sercan Basyurt: University of Potsdam
Stefan Stieglitz: University of Potsdam
Christoph Neuberger: Free University of Berlin

Information Systems Frontiers, 2025, vol. 27, issue 4, No 6, 1425-1443

Abstract: 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.

Keywords: 2019 European parliament election; Social media analytics; User’s voting prediction; Agenda-setting theory; Political agenda (search for similar items in EconPapers)
Date: 2025
References: Add references at CitEc
Citations:

Downloads: (external link)
http://link.springer.com/10.1007/s10796-024-10568-w Abstract (text/html)
Access to the full text of the articles in this series is restricted.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:infosf:v:27:y:2025:i:4:d:10.1007_s10796-024-10568-w

Ordering information: This journal article can be ordered from
http://www.springer.com/journal/10796

DOI: 10.1007/s10796-024-10568-w

Access Statistics for this article

Information Systems Frontiers is currently edited by Ram Ramesh and Raghav Rao

More articles in Information Systems Frontiers from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().