4,760 political ads from the final four weeks of the 2021 German federal election campaign on Meta platforms Facebook and Instagram. The dataset combines manual content analysis of ad tailoring with the Meta Ad Targeting Dataset for six German parties and their top candidates. It was created by Christina Gahn to measure and analyze distinct advertising strategies.
Use Cases
- Analyze the relationship between ad impressions and specific targeting criteria from the Meta Ad Targeting Dataset.
- Measure the prevalence of content tailoring strategies across different political parties using manual content analysis labels.
- Model the independent effects of targeting and tailoring strategies on campaign ad visibility metrics.
- Compare advertising strategies, such as audience selection and message adaptation, between parties and top candidates.
Strengths
- Contains 4,760 unique political advertisements.
- Covers a defined four-week period during a major national election.
- Integrates two independent data sources: manual content analysis and platform targeting data.
Limitations
- Limited to one election cycle (2021) and one country (Germany).
- Sample size of 4,760 ads may be insufficient for fine-grained sub-group analyses.
- Relies on manual coding for tailoring, which may introduce coder subjectivity.
Provenance
- Source
- Harvard Dataverse, authored by Christina Gahn.
- Collection Method
- Manual content analysis combined with the Meta Ad Targeting Dataset.
- Time Range
- Final four weeks of the 2021 German federal election campaign.
- Freshness
- Data covers 2021; metadata last updated in 2026.
- Geography
- Germany.