An Experiment in Hiring Discrimination Via Online Social Networks
Carnegie Mellon University - Heinz College
Christina M. Fong
Carnegie Mellon University - Department of Social and Decision Sciences
July 17, 2015
We investigate whether personal information posted by job candidates on social media sites is sought and used by prospective employers. We create profiles for job candidates on popular social networks, manipulating information protected under U.S. laws, and submit job applications on their behalf to over 4,000 employers. We find evidence of employers searching online for the candidates. After comparing interview invitations for a Muslim versus a Christian candidate, and a gay versus a straight candidate, we find no difference in callback rates for the gay candidate compared to the straight candidate, but a 13% lower callback rate for the Muslim candidate compared to the Christian candidate. While the difference is not significant at the national level, it exhibits significant and robust heterogeneity in bias at the local level, compatible with existing theories of discrimination. In particular, employers in Republican areas exhibit significant bias both against the Muslim candidate, and in favor of the Christian candidate. This bias is significantly larger than the bias in Democratic areas. The results are robust to using state- and county-level data, to controlling for firm, job, and geographical characteristics, and to several model specifications. The results suggest that 1) the online disclosure of certain personal traits can influence the hiring decisions of U.S. firms and 2) the likelihood of hiring discrimination via online searches varies across employers. The findings also highlight the surprisingly lasting behavioral influence of traditional, offline networks in processes and scenarios where online interactions are becoming increasingly common.
Number of Pages in PDF File: 38
Keywords: Privacy, Economics, Social Networking Sites, Labor Discrimination
JEL Classification: J7
Date posted: April 2, 2012 ; Last revised: March 12, 2016
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