Can social media lead to labor market discrimination? Evidence from a field experiment

• Date: 01 April 2019
• Published date: 01 April 2019
• DOI: http://doi.org/10.1111/jems.12291

Received: 28 August 2017

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Revised: 4 May 2018

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Accepted: 22 July 2018

DOI: 10.1111/jems.12291

ORIGINAL ARTICLE

Can social media lead to labor market discrimination?

Evidence from a field experiment

Matthieu Manant*

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Serge Pajak

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Nicolas Soulié

RITM, Université Paris‐Sud, Université

Paris‐Saclay, Sceaux, France

Correspondence

Matthieu Manant, RITM, Université

Paris‐Sud, Université Paris‐Saclay,

Sceaux, France.

Email:matthieu.manant@u-psud.fr

Funding information

Agence Nationale de la Recherche, Grant/

Award Number: ANR‐10‐CORD‐0002

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 change, a significant

41.7% gap between the two applicants callback rates highlights that personal

online profiles are used by recruiters as a source of information to discriminate

against applicants of foreign origin. After the layout change that mitigates our

signal, the difference in callback rates fades away. This result suggests that the

screening conducted by the employers does not go beyond the main pages of

profiles. It also illustrates that design choices made by online platforms may

have important consequences on the extent of discrimination.

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INTRODUCTION

Discrimination based on race and ethnic background, or more generally on personal traits, is a major concern. The

spread of social media has made disclosing personal information and traits online a daily habit for hundreds of millions

of people.

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This makes social media attractive to recruiters looking for information on job applicants that does not

appear on the application material. While information unrelated to applicants’professional skills might help improving

the match between applicants and recruiters, it leaves room for discrimination. In the case of social media used for

leisure purposes, for example, Facebook, users often disclose information without considering potential professional

consequences. Bertrand and Duflo (2017) highlight that the impact of social media on hiring discrimination has been

largely overlooked in the economic literature so far, although documenting such practices is essential since the

discrimination occurs without the applicants awareness.

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In this paper, we propose an experimental setting to assess

whether information disclosed on social media constitutes a source of discrimination during hiring. More precisely, we

J Econ Manage Strat. 2019;28:225–246. wileyonlinelibrary.com/journal/jems © 2018 Wiley Periodicals, Inc.

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*This paper was presented at the Telecom ParisTech Economics and Management Seminar (January 2013), the University Paris‐Est Créteil seminar

(January 2013), the Economics and Psychology seminar at Paris School of Economics (March 2013), the 3rd SEEK Conference on Labour Market at

ZEW Mannheim (April 2013), the 11th IIOC Annual Conference in Boston (May 2013), the Workshop on Experimental Economics in Florence (May

2013), the 4th Annual Meeting of the French Experimental Economics Association in Lyon (June 2013), the 62nd Annual Meeting of the French

Economic Association in Aix‐en‐Provence (June 2013), the World Meeting of the Economic Science Association in Zurich (July 2013), the Annual

Conference of the European Association of Law and Economics in Warsaw (September 2014), the 29th Annual Conference of the European

Economic Association in Toulouse (August 2014), the 6th Annual Meeting of the French Experimental Economic Association in Paris (June 2015),

the 30th Annual Conference of the European Economic Association in Mannheim (August 2015), the Amsterdam Privacy Conference (October 2015),

the LED Université Paris 8 seminar (January 2017), and the Advances in Field Experiments Conference in Chicago (September 2017).

investigate whether recruiters discriminate against job applicants on the basis solely of the information they find on

Facebook profiles.

Intheliteratureonlabormarketdiscrimination, the negative impact on hiring of personal traits linked to

minority groups has been well documented for the sexual orientation, religious beliefs, and political opinions (see

Bertrand & Duflo, 2017; Riach & Rich, 2002). In addition, the negative effect of belonging to a racial minority has

been widely studied and observed worldwide. Recruiters generally gather information on applicants from their

application materials (resume, cover letter, etc.), during the interview, or via word‐of‐mouth (Granovetter, 1995;

Rees, 1966). A distinct feature of our study is that the personal traits we use are not disclosed by any of these usual

channels.

The personal traits disclosed by individuals on social media are not revealed for professional purposes but rather to

entertain friends and relatives in a broad sense. Several scholars have pointed to the effect of the Internet on labor

markets (Autor, 2001; Kuhn & Mansour, 2014). In relation to the hiring process, Clark and Roberts (2010) review

declarative surveys, which document the emerging use of social media by recruiters to screen applicants. Those

practices vary widely among the different surveys due most probably to declarative bias stemming from the illegality of

these practices. It has been shown in other contexts such as the short‐term housing rental market (Edelman, Luca, &

Svirsky, 2017), online commerce (Doleac & Stein, 2013), and peer‐to‐peer loans (Pope & Sydnor, 2011) that online

information found by recruiters can be used to discriminate. The paper by Acquisti and Fong (2016) is closest to our

article. They use a field experiment to address the issue of discrimination during hiring based on online information in

the US labor market, and find evidence of such discriminatory practices with respect to religious beliefs in some states

and counties. Their project is concurrent but independent from ours.

In this paper, we test the use of social media by recruiters to discriminate in hiring decisions, based on a field

experiment on the French labor market. We created two fictitious applicants, which differ in one signal—their

perceived origins—which is available only on their Facebook profiles. The control applicant has a typically French

profile, while the test applicant’s profile reveals that he is from Marrakesh, Morocco (North Africa), and speaks

Moroccan Arabic, and so is perceived as a candidate of Arabic origin. People of Arabic descent are a minority in France,

and numerous studies on the labor market in France and in other countries show that people of Arabic origin are

subject to hiring discrimination.

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Each applicant was given a unique first name and last name combination on social

media to ensure that an Internet search would identify the right profile. Our candidates applied for job positions at an

accountant in the greater Paris area. We sent one application per job opening using pseudo-random assignment method

(see Ahmed, Andersson, & Hammarstedt, 2013; Acquisti & Fong, 2016). Sending one application per job opening

alleviates risk of detection, and further reduces the burden on recruiters imposed by the experiment. It also allows us to

use identical application materials, resumes, and cover letters, for both applicants.

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The pseudo-random assignment

method allows us to control, during the experiment, that the two fictitious candidates are applying for similar job

positions. Following the literature on hiring, we consider a callback from a recruiter to set up a job interview as a

positive outcome. Since the two applicants are similar except for their perceived origins displayed only on their

Facebook profiles (hometown and spoken languages), a significant difference in callback rates can stem only from the

observation by the potential employer of this signal, and the use of it to discriminate.

Using our two fictitious applicants, we applied for more than 800 positions over a 12‐month period between March

2012 and March 2013, including the main experiment and two robustness checks. For the main experiment between

March and September 2012, we sent 462 applications, equally divided between the two applicants. We find significantly

different response rates for our two fictitious applicants: 21.3% for the French candidate, and 13.4% for the Arabic

applicant. This gap in callback rates in favor of the French (vs. the Arabic) applicant suggests that in addition to the

information in the application material, employers search for other information on applicants, and use the information

found on Facebook profiles to discriminate. In our case, a small signal on the Facebook profile generates a significant

and constant gap of 37% in the probabilities of our two applicants of being called back for interview.

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Thus, personal

information posted on Facebook has a dramatic effect on the odds of being called for an interview. In other words, we

show that recruiters use information found on Facebook profiles to discriminate among applicants.

We also conduct two robustness checks. First, we test for alternative names, and obtain similar results which shows

that our main result does not rely on the applicants’names. Second, an exogenous change in December 2012 in the

default layout of the Facebook profiles allows us to confirm that the gap between our two applicants relies on

the differentiating signal (perceived French origin vs. Arabic origin). The layout change results in a part of our signal,

the spoken languages, being located under a secondary tab rather than being displayed on the front page of profiles.

After December 2012, the gap in callback rates between the two candidates shrank dramatically, as though in the

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