The strategic use of microtargeting: The case of the German Federal Elections of 2025

Stefan Repp

No 270/2026, IPE Working Papers from Berlin School of Economics and Law, Institute for International Political Economy (IPE)

Abstract: Political microtargeting (PMT) is often associated with data-intensive voter profiling and the Cambridge Analytica scandal. This paper argues that such a framing is increasingly outdated, particularly in tightly regulated contexts. Drawing on expert interviews, social media content analysis and digital advertising spending data from the 2025 German federal election, we show that PMT has not disappeared under stricter European regulation but has fundamentally changed its form. Constrained by the GDPR and the Transparency and Targeting of Political Advertising regulation, parties largely abandoned direct psychographic profiling. Yet targeted political communication remained highly effective through a different mechanism: algorithmic amplification. Platforms such as TikTok, Instagram and YouTube systematically amplified content from parties at the political margins, independent of advertising expenditure. The AfD and Die Linke achieved visibility far exceeding their paid spend, while better-funded mainstream parties underperformed in recommended feeds. Drawing on the Big Five personality model and the Persuasion Knowledge Model, this paper explains why platform-native, emotionally charged content proved so persuasive and why audiences were least likely to recognise it as targeted communication. The findings suggest that democratic oversight must shift focus from paid advertising to the design of algorithmic recommendation systems.

Keywords: political microtargeting; algorithmic amplification; online political advertising; GDPR; German federal election; persuasion knowledge; platform governance; social media campaigning (search for similar items in EconPapers)
JEL-codes: D72 D91 M37 (search for similar items in EconPapers)
Date: 2026
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Persistent link: https://EconPapers.repec.org/RePEc:zbw:ipewps:341421

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