Social Media, Web, and Panel Surveys: Using Non-Probability Samples in Social and Policy Research

Abstract

The use of online surveys has grown rapidly in social science and policy research, surpassing more established methods. We argue that a better understanding is needed, especially of the strengths and weaknesses of non-probability online surveys, which can be conducted relatively quickly and cheaply. We describe two common approaches to non-probability online surveys-river and panel sampling-and theorize their inherent selection biases: namely, topical self-selection and economic self-selection. We conduct an empirical comparison of two river samples (Facebook and web-based sample) and one panel sample (from a major survey research company) with benchmark data grounded in a comprehensive population registry. The river samples diverge from the benchmark on demographic variables and yield much higher frequencies on non-demographic variables, even after demographic adjustments; we attribute this to topical self-selection. The panel sample is closer to the benchmark. When examining the characteristics of a non-demographic subpopulation, we detect no differences between the river and panel samples. We conclude that non-probability online surveys do not replace probability surveys, but augment the researcher's toolkit with new digital practices, such as exploratory studies of small and emerging non-demographic subpopulations.