Discrimination in the Formation of Academic Networks: A Field Experiment on #EconTwitter

Abstract

This paper experimentally documents discrimination in the formation of professional networks among academic economists. We created fictitious human-like bot accounts that claimed to be PhD students in economics, differing in three characteristics: gender (male or female), race (Black or White), and university affiliation (top- or lower-ranked). The bot accounts randomly followed Twitter users who form part of the #EconTwitter academic community. Follow-back rates were 12% higher for White students compared to Black students; 21% higher for students from top-ranked universities compared to accounts of lower-ranked institutions, and 25% higher for female compared to male students. The racial gap persisted even among students from top-ranked institutions, suggesting that Twitter users racially discriminate even in the presence of a signal that could be interpreted as indicative of higher academic potential. Notably, we find that Black male students from top-ranked universities receive no more follow-backs than White male students from lower-ranked institutions

Keywords: Discrimination, Economics Profession, Gender, Race, Social Media

JEL Classification: J15, J16, A11, C93, I23