Privacy and political online microtargeting during the German Federal Election 2021*
Johanna Börsting,
Regine Frener and
Sabine Trepte
Behaviour and Information Technology, 2025, vol. 44, issue 12, 3097-3114
Abstract:
In the context of Federal Elections, political parties frequently engage in targeting social media users with tailored content. To facilitate this, personal data must be collected and processed, often without the users’ explicit awareness. Many users view political online microtargeting as an intrusion upon their privacy. In a longitudinal time-based sampling study shortly before, during, and after the German Federal Election in 2021, we surveyed social media users (N = 126) about their perception of political online microtargeting and individual privacy. In particular, we evaluated participants’ perception of being targeted, perceived social media affordances (anonymity, association), availability of privacy mechanisms (control, trust, norms, communication), and their subjective experience of privacy (experienced level of access, privacy perception). Furthermore, we evaluated how these variables influence users’ privacy regulation behaviours (interdependent or egocentric), political self-efficacy, future political information behaviour, and voting behaviour in the light of political online microtargeting. Multilevel analyses revealed that it is difficult for users to detect targeted ads, but that they feel more private and self-efficacious in their political and future political information behaviour if they believe they can rely on privacy mechanisms such as trust and control.
Date: 2025
References: Add references at CitEc
Citations:
Downloads: (external link)
http://hdl.handle.net/10.1080/0144929X.2024.2431052 (text/html)
Access to full text is restricted to subscribers.
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:taf:tbitxx:v:44:y:2025:i:12:p:3097-3114
Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/tbit20
DOI: 10.1080/0144929X.2024.2431052
Access Statistics for this article
Behaviour and Information Technology is currently edited by Dr Panos P Markopoulos
More articles in Behaviour and Information Technology from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().