#InviteMe: Can social media information reduce discrimination? Evidence from a field experiment Author Raphael Moritz, Christian Manger, Kerstin Pull Publication Year 2023 Type Journal Article Abstract We study whether and to what extent social media information can reduce (ethnic) discrimination in a two-sided market characterized by asymmetric information. We analyze whether information that breaks with prevailing ethnic stereotypes might induce the uninformed side of the market to update its probabilistic beliefs on a desired, but hidden quality of an ethnic minority applicant. We create eight social media profiles (male and female) and apply for 3,676 vacant room ads for shared housing on a two-sided platform. The profiles are each identical within one gender, except for the different names assigned to them: two profiles of each gender are assigned a Turkish-sounding name, two a German-sounding name. To each application, we randomly assign one of the eight names and whether it contains a link to the corresponding social media profile. When an application includes such a link, the otherwise substantial discrimination against applicants with Turkish-sounding names is not only significantly reduced, but almost eliminated –- hinting at the potential of social media information that breaks with prevailing stereotypes to reduce (statistical) discrimination. (PsycInfo Database Record (c) 2023 APA, all rights reserved) Keywords social media, Ethnic discrimination, stereotypes, field experiment, Housing market, Information systems, names, race and ethnic discrimination, stereotyped attitudes Journal J. Econ. Behav. Organ. Volume 213 Pages 373–393 Date Published 09/2023 Full text A description of data collection and analysis can be found in the pre-registration for this study: https://www.socialscienceregistry.org/trials/7627/history/179993 Type of Prejudice/Bias Race/Ethnicity Country Germany Method Field Setting Online Google ScholarBibTeX