Abstract:In this paper, we investigate the role of social media as a source of information for recruiters to discriminate applicants. We set up a field experiment over a 12‐month period, involving more than 800 applications from two fictitious applicants which differed in their perceived origins, which is an information available only from their Facebook profiles. During the experiment, an unexpected change in the Facebook layout reduced the salience of the information available on social media profiles. Before this ch… Show more
“…As for policy implication, one might wonder if a policy prohibiting a photo from CV could help reduce discrimination against appearance. In France, Manant et al (2014) found that despite having no photo on the CV, recruiters did gather information about their fictitious candidates' looks and religious practice from their Facebook profiles.…”
This paper investigates effects of appearance and religious practice of job applicants on the hiring decision. We asked participants in our laboratory experiment to select fictitious candidates for an interview from a pool of CVs with comparable characteristics but different photos. Some photos were of the same Turkish women with and without a headscarf. We demonstrate the effects of appearance, ethnicity, and veiling simultaneously and propose underlying mechanisms. We find robust effects of appearance but heterogeneous effects of headscarf on callback rates based on types of occupations and recruiters' characteristics. However, positive characteristics mitigate discrimination against headscarf and even reverse it. JEL Classification: J15, J71, C91
“…As for policy implication, one might wonder if a policy prohibiting a photo from CV could help reduce discrimination against appearance. In France, Manant et al (2014) found that despite having no photo on the CV, recruiters did gather information about their fictitious candidates' looks and religious practice from their Facebook profiles.…”
This paper investigates effects of appearance and religious practice of job applicants on the hiring decision. We asked participants in our laboratory experiment to select fictitious candidates for an interview from a pool of CVs with comparable characteristics but different photos. Some photos were of the same Turkish women with and without a headscarf. We demonstrate the effects of appearance, ethnicity, and veiling simultaneously and propose underlying mechanisms. We find robust effects of appearance but heterogeneous effects of headscarf on callback rates based on types of occupations and recruiters' characteristics. However, positive characteristics mitigate discrimination against headscarf and even reverse it. JEL Classification: J15, J71, C91
“…The authors of [1] find no significant discrimination due family structure and sexual orientation, while a negative effect is elicited for radical religious stance. The supposed origin of the user is found to have a significant effect on the number of replies a person gets to a job application [34]. The chances to obtain short-term accommodation online are influenced by the assumed racial origin [14].…”
Section: Related Workmentioning
confidence: 99%
“…Below, we illustrate contexts in which users' lives are influenced by their online activity. The authors of [1] and [34] create fictitious Facebook profiles in which they vary only one type of personal data to assess its influence during job search. The authors of [1] find no significant discrimination due family structure and sexual orientation, while a negative effect is elicited for radical religious stance.…”
Social networks give free access to their services in exchange for the right to exploit their users' data. Data sharing is done in an initial context which is chosen by the users. However, data are used by social networks and third parties in different contexts which are often not transparent. We propose a new approach which unveils potential effects of data sharing in impactful real-life situations. Focus is put on visual content because of its strong influence in shaping online user profiles. The approach relies on three components: (1) a set of concepts with associated situation impact ratings obtained by crowdsourcing, (2) a corresponding set of object detectors used to analyze users' photos and (3) a ground truth dataset made of 500 visual user profiles which are manually rated for each situation. These components are combined in LERV U P , a method which learns to rate visual user profiles in each situation. LERV U P exploits a new image descriptor which aggregates concept ratings and object detections at user level. It also uses an attention mechanism to boost the detections of highly-rated concepts to prevent them from being overwhelmed by low-rated ones. Performance is evaluated per situation by measuring the correlation between the automatic ranking of profile ratings and a manual ground truth. Results indicate that LERV U P is effective since a strong correlation of the two rankings is obtained. This finding indicates that providing meaningful automatic situation-related feedback about the effects of data sharing is feasible.
“…Social media screening of applicants may induce bias (Wade et al 2020) and discrimination (Manant et al 2019) for a variety of reasons. One source of discrimination against applicants is the demographic information published on a social media profile.…”
Section: Bias Suppressionmentioning
confidence: 99%
“…In most social media screening contexts, applicants are unaware that the employer uses social media screening, to what extent information is gathered from social networks, and how strongly it influences hiring decisions (Jeske and Shultz 2016;McDonald and Thompson 2016). Thus, many rejected applicants are never told that an adverse decision was made on the basis of social media screening (Clark and Roberts 2010), and discrimination may occur without the applicant's knowledge (Manant et al 2019). Therefore, the screening of online sources is considered as an "extractive" rather than an "interactive" search for information, as it does not involve two-way communication with the applicant (Berkelaar 2014(Berkelaar , 2017Berkelaar and Buzzanell 2014).…”
Companies have started using social media for screening applicants in the selection process. Thereby, they enter a low-cost source of information on applicants, which potentially allows them to hire the right person on the job and avoid irresponsible employee behaviour and negligent hiring lawsuits. However, a number of ethical issues are associated with this practice, which give rise to the question of the fairness of social media screening. This article aims to provide an assessment of the procedural justice of social media screening and to articulate recommendations for a fairer use of social media in the selection process. To achieve this, a systematic literature review of research articles pertaining to social media screening has been conducted. Thereby, the benefits and ethical issues relating to social media screening, as well as recommendations for its use have been extracted and discussed against Leventhal’s (1980) rules of procedural justice. It turns out that without clear guidelines for recruiters, social media screening cannot be considered procedurally fair, as it opens up way too many opportunities for infringements on privacy, unfair discrimination, and adverse selection based on inaccurate information. However, it is possible to enhance the fairness of this practice by establishing clear policies and procedures to standardize the process.
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