Replication Data for: Quota Sampling Using Facebook Advertisements

Researchers in different social science disciplines have successfully used Facebook to recruit subjects for their studies. However, such convenience samples are not generally representative of the population. We develop and validate a new quota sampling method to recruit respondents using Facebook advertisements, and publish an R package to semi-automate this quota sampling process using the Facebook Marketing API. To test the method, we used Facebook advertisements to quota sample 2432 U.S. respondents for a survey on climate change public opinion. We conducted a contemporaneous nationally representative survey asking identical questions using a high-quality online survey panel whose respondents were recruited using probability sampling. Many results from the Facebook-sampled survey are similar to those from the online panel survey; furthermore, results from the Facebook-sampled survey approximate results from the American Community Survey (ACS) for a set of validation questions. These findings suggest that using Facebook to recruit respondents is a viable option for survey researchers wishing to approximate population-level public opinion.

不同社会科学学科的研究者已成功依托脸书（Facebook）开展研究受试者招募工作。但此类便利样本通常不具备总体代表性。我们开发并验证了一种全新的配额抽样方法，可通过脸书广告招募受访者，并发布了一款R语言包，借助脸书营销API（Facebook Marketing API）实现该配额抽样流程的半自动化。为验证该方法，我们通过脸书广告为一项气候变化公众舆论调查配额抽样了2432名美国受访者。同期，我们采用高质量在线调查面板（其受访者通过概率抽样招募）开展了全国代表性调查，并使用完全一致的问卷题目。脸书抽样调查的多项结果与在线面板调查结果高度相似；此外，在一组验证问题上，脸书抽样调查的结果近似于美国社区调查（American Community Survey, ACS）的结果。上述研究结果表明，对于希望近似反映总体层面公众舆论的调查研究者而言，依托脸书招募受访者是一种可行的方案。