Speaker: Yingxin Lin (Ph.D. Candidate at the Chinese University of Hong Kong)

Date & Time: Fri. 19, December 2025, from 10:00 to 11:30 AM (Beijing Time)

Location: Tongji Building A2101

ABSTRACT

To enhance verifiability and reduce information asymmetry, online labor platforms prevalently encourage freelancers to post personalized profile pictures. Using observational data from Upwork, we investigate how positive facial expressions in freelancers’ profile pictures (e.g., smiles), which were intended to increase media richness and hiring efficiency, unexpectedly reinforce gender inequality. We find that smiles in profile pictures increase job access for male freelancers but not for female freelancers, significantly contributing to the overall gender gap favoring males. Similarly, smiling widens the gender gap in income and the likelihood of being invited by peers to join freelancer agencies, disproportionately benefiting male freelancers. Moreover, we identify three moderators that platform designers can leverage to mitigate this unequal impact of smiles: convergent (vs. divergent) historical performance ratings, male-dominated (vs. other) occupational categories, and lower (vs. higher) socioeconomic location labels. Follow-up experiment not only reconfirms our findings but also reveals the key mechanism behind, namely, gender stereotypes that assume women are intrinsically more emotionally expressive than men. These stereotypes are activated by the combination of gender cues and facial emotional expressiveness in profile pictures, eliciting inattention to female freelancers’ smiles. We further rule out two potential alternative explanations. Finally, we discuss the theoretical and practical implications.

Keywords: Online labor platforms, gender gap, stereotypes, facial emotional expressiveness, media richness theory, social vision theory, gender inequality, gig economy