Date of Award

Winter 2-2022

Document Type

Dissertation

Degree Name

Doctor of Philosophy (PhD)

First Advisor

Steven Toaddy

Abstract

Recent research has shown that the rate of use of Social Networking Sites (SNSs) for recruitment, screening, and selection purposes is rising steadily (Alexander et al., 2019; CareerArc, 2021; SHRM, 2013), prompting many to call for research regarding the fairness and effectiveness of SNSs for these purposes (Alexander et al., 2019; Blacksmith & Poeppelman, 2014; Davison et al., 2011; Davison et al., 2012; Dwyer et al., 2007). The current study focuses on LinkedIn, a SNS designed specifically to connect working professionals and explores implicit racial discrimination in hiring. Implicit racial discrimination occurs when an individual unconsciously treats another individual prejudicially based on perceived or actual racial-group membership. The current study examined whether participants with at least some hiring experience (representing “employers” in this study) provided higher employability ratings and starting salary estimates to applicants whose race reflected their own compared to applicants whose race did not reflect their own. Participants were randomly assigned to groups wherein each group was shown an identical job description and then asked to rate LinkedIn profiles differing only in one aspect: the race of the applicant. Each participant rated a LinkedIn profile displaying a picture of either a white, black, or Hispanic applicant, and for the purposes of the study were coded as either matching or not matching the applicant’s race (one independent variable, two levels).

The same picture of the same individual was used for each LinkedIn profile, his skin tone changed with photo-editing software to approximate each race. Participants did not assign significantly higher ratings of employability or a higher proposed salary to LinkedIn profiles containing an applicant picture that matched their race.

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