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.

中文翻译：

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社交媒体，Web和面板调查：在社会和政策研究中使用非概率样本

在社会科学和政策研究中，在线调查的使用已迅速增长，超过了更成熟的方法。我们认为需要更好的理解，尤其是对非概率在线调查的优缺点的了解，可以相对快速，廉价地进行。我们描述了两种非概率在线调查的常用方法，即河流抽样和面板抽样，并从理论上解释了其固有的选择偏差：即主题自我选择和经济自我选择。我们对两个河流样本（Facebook和基于网络的样本）和一个面板样本（来自大型调查研究公司）进行了实证比较，其基准数据以全面的人口登记册为基础。河流样本在人口变量上与基准不同，在非人口变量上产生更高的频率，即使在人口结构调整后；我们将此归因于主题的自我选择。面板样本更接近基准。在检查非人口统计学子种群的特征时，我们发现河流样本和面板样本之间没有差异。我们得出的结论是，非概率在线调查不能代替概率调查，而是通过新的数字实践（例如对小型和新兴的非人口子群体的探索性研究）来扩大研究人员的工具包。