Social media sampling is an effective way to access hard to survey populations and low prevalence groups

Dennis Klinke, Jannes Jacobsen, Manuel Dierse, Thorsten Faas, Denis Gerstorf, Hannah Helal, Swen Hutter, David Schieferdecker, Hanna Schwander, Christian von Scheve and Jule Specht

EconStor Open Access Articles and Book Chapters, 2025, issue Latest Articles, 20 pages

Abstract: Non-probability samples have become increasingly popular despite some criticism. This paper examines social media sampling as a tool for accessing hard-to-survey populations. Our study targeted individuals in Germany using ads on Facebook and X, yielding 4,590 respondents. We compared these samples with high-quality probability samples (SOEP, ESS) through measurement equivalence analysis of shared measures between samples. Results show that our social media sampling strategy yielded effective sample sizes for our target population that exceeded those from SOEP and ESS by ratios between 2:1 and 5:1. Our findings suggest that non-probability sampling can be a viable method for researchers examining relational patterns among variables in hard-to-survey populations. Because we observe varying levels of measurement equivalence, rigorous methodological strategies for post-hoc analyses are recommended. We propose measurement equivalence analysis as a post-hoc assessment strategy to quantify the analytical effectiveness of the employed sampling strategy.

Keywords: Probability sampling; non-probability sampling; social media sampling; survey methodology; measurement invariance (search for similar items in EconPapers)
Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:zbw:espost:331212

DOI: 10.1080/13645579.2025.2564866

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