"Talking past each other": Issue ownership and microtargeting in Swiss online political ads

2025-12-16

AI Summary

This study investigates how issue ownership and microtargeting of online political advertising in Switzerland’s direct democracy affect public opinion and referendum outcomes, specifically examining whether such practices exacerbate public sphere fragmentation and undermine democratic deliberation. Method: Leveraging 40,000 Facebook/Instagram political ads from 2021–2025, the analysis integrates multilevel demographic modeling, XGBoost classification, semantic issue clustering, and spatial disparity analysis. Contribution/Results: The study provides the first empirical evidence of “talking past each other” — a fragmented issue-ownership pattern across parties. It identifies pronounced geographic divergence in party-level targeting strategies and uncovers a four-dimensional targeting logic (age, gender, party affiliation, and canton). A predictive model classifies ad-sponsoring parties with 89% accuracy. Crucially, exposure to pro-referendum ads is significantly positively associated with referendum passage rates, highlighting the tangible electoral impact of microtargeted issue framing.

Technology Category

• Natural Language Processing: Discourse, Pragmatics & Argument Mining
• Application Domains: Misinformation & Fake News
• Humans and AI: Voting

Application Category

• User Modeling, Personalization and Recommendation: User modeling for targeted and personalized online advertising
• Social Networks and Social Media: Media and governance, opinion dynamics, filter bubbles, polarization
• Responsible Web: Consent frameworks and practices on the web

Abstract

Switzerland's unique system of direct democracy, characterized by frequent popular referenda, provides a critical context for studying the impact of online political advertising beyond standard electoral cycles. This paper presents a large-scale, data-driven analysis of 40k political ads published on Facebook and Instagram in Switzerland between 2021 and 2025. Despite a voting population of only 5.6 million, the ad campaigns were significant in scale, costing CHF 4.5 million and achieving 560 million impressions. This study shows that political ads are used not only for federal elections, but also to influence referenda, where greater exposure to ``pro-Yes'' advertising correlates significantly with approval outcomes. The analysis of microtargeting reveals distinct partisan strategies: centrist and right-wing parties predominantly target older men, whereas left-wing parties focus on young women. Furthermore, significant region-specific demographic variations are observed even within the same party, reflecting Switzerland's strong territorial divisions. Regarding content, a clear pattern of ``talking past each other'' is identified: in line with issue ownership theory, parties avoid direct debate on shared issues, preferring to promote exclusively owned topics. Finally, it is demonstrated that these strategies are so distinct that an ad's author can be predicted using a machine learning model trained exclusively on its audience and topic features. This study sheds light on how microtargeting and issue divergence on social platforms may fragment the public sphere and bypass traditional democratic deliberation.

Problem

• Analyzing microtargeting strategies in Swiss online political ads
• Examining issue ownership and content divergence in referendum campaigns
• Investigating demographic targeting variations across parties and regions

Innovation

• Large-scale data analysis of Swiss online political ads
• Microtargeting strategies reveal distinct partisan demographic focuses
• Machine learning predicts ad authorship from audience and topic features