User Roles in Online Political Discussions : a Typology based on Twitter Data from the German Federal Election 2017

Title data

Gimpel, Henner ; Hamann, Florian ; Schoch, Manfred ; Wittich, Marcel:
User Roles in Online Political Discussions : a Typology based on Twitter Data from the German Federal Election 2017.
2018
Event: 80. Jahrestagung des Verbands der Hochschullehrer für Betriebswirtschaft (VHB 2018) , 23.05. - 25.05.2018 , Magdeburg, Deutschland.
(Conference item: Conference , Paper )

Official URL:

Abstract in another language

Twitter is well recognized as a microblogging site, an online social network (OSN), and increasingly as a digital news platform. With the changing media usage behavior over the past decade, political actors have now recognized the need to enrich their election campaign efforts by including social media strategies. However, previous research has shown that users behave heterogeneously in online political discussions. To better understand how users behave and interact in such debates, we conduct an exploratory study to identify emergent user roles from Twitter data. We develop a dynamic selection query to collect a representative data set on the German federal election of 2017.
We define features of structure, function, and time for Twitter discussions and conduct a cluster analysis to derive eleven emergent roles from the 30,553 most active users. We then refine those roles by further data-driven analyses to enhance and deepen their understanding. Our results indicate dominance of the online discussion by the populist party Alternative für Deutschland. We also find that media outlets and political parties show somewhat similar behavior, and that the offline popularity of prestigious actors is extended into the online world.

Further data

Item Type:	Conference item (Paper)
Refereed:	Yes
Institutions of the University:	Faculties > Faculty of Law, Business and Economics > Department of Business Administration Research Institutions Research Institutions > Affiliated Institutes Research Institutions > Affiliated Institutes > FIM Research Center Finance & Information Management Faculties Faculties > Faculty of Law, Business and Economics
Result of work at the UBT:	No
DDC Subjects:	000 Computer Science, information, general works > 004 Computer science 300 Social sciences > 330 Economics
Date Deposited:	18 Sep 2018 08:03
Last Modified:	25 Oct 2019 08:38
URI:	https://eref.uni-bayreuth.de/id/eprint/45822