Twitter's Glass Ceiling: The Effect of Perceived Gender on Online Visibility

Shirin Nilizadeh, Anne Groggel, Peter Lista, Srijita Das, Yong-Yeol Ahn, Apu Kapadia, and Fabio Rojas

In Proceedings of The International AAAI Conference on Web and Social Media (ICWSM '16), Cologne, Germany, May 17–20, 2016.

Social media is a new public sphere where people can, in principle, communicate with each other regardless of their status. However, social categories like gender may still bias online communication, replicating offline disparities. Examining over 94,000 Twitter users, we investigate the association between perceived gender and measures of online visibility: how often Twitter users are followed, assigned to lists, and retweeted. Our analysis shows that users perceived as female experience a 'glass ceiling,' similar to the barrier women face in attaining higher positions in companies. For users in lower quartiles of visibility, being perceived as female is associated with more visibility; however, this tendency flips among the most visible users where being perceived as male is strongly associated with more visibility. Our results suggest that gender presented in social media profiles likely frame interactions as well as perpetuates old inequalities online.


Data mining, Name-based and photo-based gender detection, Data Analysis: quartile regression, multivariate regression models such as poisson, linear, and negative binomial regression models.