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Facebook Ads Can Approximate Representative US Public Opinion on Climate Change
Insights from the Field
quota sampling
facebook ads
us public opinion
acs validation
Methodology
PSR&M
3 R files
5 datasets
5 PDF files
2 text files
Dataverse
Quota Sampling Using Facebook Advertisements was authored by Baobao Zhang, Matto Mildenberger, Peter D. Howe, Jennifer Marlon, Seth Rosenthal and Anthony Leiserowitz. It was published by Cambridge in PSR&M in 2020.

Researchers often rely on convenience samples via social media like Facebook, but these aren't typically representative of the broader population. This article introduces a new quota sampling method using targeted Facebook advertisements to achieve more balanced representation.

Data & Methods: Used randomized controlled trials and probability weighting within Facebook's Marketing API for semi-automated recruitment.

Key Findings: Compared survey results on climate change opinions from their Facebook-sampled group (2,432 US respondents) with a contemporaneous national panel survey using random sampling.

* The findings largely align across key metrics despite being convenience samples.

* The Facebook-recruited data approximates official government statistics like the American Community Survey for several validation questions.

Why It Matters: This approach provides political scientists and social researchers with a more accessible alternative to traditional probability sampling methods while still achieving population-level insights.

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Political Science Research & Methods
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