Gender bias and crowd-sourced financial information
Authors | Bhagwat, Dim, Shirley, Stark |
Year | 2023 |
Type | Working Paper |
Abstract | The capacity to aggregate information from diverse perspectives has positioned social finance forums as a potent source of signals that shape investors' beliefs. We study the Seeking Alpha forum to determine if female contributors face a more hostile environment than males and the consequences for effective information aggregation. We find that although male and female contributors display similar abilities, female-authored perspectives receive significantly lower engagement and trust from platform users. Females also face more heightened disagreement and attract more online trolls. This combative environment results in more female contributors quitting the platform, eroding the informativeness of the platform consensus, and implies relatively lower financial compensation for female contributors. |
Keywords | Gender bias, social finance, social media, FinTech, information aggregation, disagreement |
URL | https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4669864 |
Tags | Archival Empirical | Asset Pricing, Trading Volume and Market Efficiency | Propagation of Noise / Undesirable Outcomes |