This article proposes sampling strategies for video-based research, improving guidelines for social scientists.
Large-N, inference-based approaches are gaining increasing prominence in video-based social science research across sociology, social psychology, political science, and other fields. However, existing methodological publications on video methods do not discuss sampling methodology and empirical video-based research often includes only cursory discussions of the issue. To address this gap, this article applies insights from sampling methodology to video-based social science research. We review how sampling has been addressed in video-based social science research, reflect on its specific challenges, and propose a decision-tree flowchart to help researchers identify appropriate sampling strategies and common pitfalls. We then illustrate how the flowchart can be used in three common video-based sampling scenarios. The article thereby contributes to establishing clear guidelines for sampling in video-based social research as a reference point and as a resource for current and future practitioners, as well as reviewers and readers of such studies.
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Legewie et al. (2026) studied this question.
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