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
October 26, 2014
Online services offer workers and firms a new channel for job market searching and matching. However, little is known about how job candidates’ online information influences employers’ hiring decisions. Leveraging and advancing a methodology common in résumé studies, we investigate how the hiring behavior of U.S. employers is affected by their online search activity and the information they find online about job candidates. We create profiles for job candidates on popular online social networks, manipulating information that is protected under either federal or state laws but that may be inferred from individuals’ online presences. We submit job applications on behalf of the candidates to over 4,000 U.S. employers, and compare interview invitations for a Muslim candidate relative to a Christian candidate, as well as a gay candidate relative to a straight candidate. We estimate that a minority of U.S. employers searched online for the candidates’ information. We find that discrimination against the Muslim candidate relative to the Christian candidate significantly varies with employer characteristics. Employers in areas with higher proportions of Republican voters were significantly less likely to call back the Muslim candidate. The results are robust to using either state- or county-level data, to controlling for firm, job, and geographical characteristics, and to various model specifications. The findings suggest that hiring discrimination via online searches of candidates may not be widespread, but online disclosures of personal traits can significantly influence the hiring decisions of a self-selected set of employers.
Number of Pages in PDF File: 81
Keywords: Economics, Field Experiments, Labor Discrimination, Online Social Networks, Privacy
JEL Classification: J7
Date posted: April 2, 2012 ; Last revised: October 26, 2014
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