Stanford Research: X Algorithm Prioritizes Outrageous Content to Boost Engagement

Summary

A study published in PNAS found that X's recommendation algorithm tends to prioritize content inconsistent with users' values, i.e., anger-inducing content, to increase engagement, forming a cycle of 'more anger, more interaction, more recommendations.' Conducted by Stanford and other institutions, the study involved 715 U.S. users who installed browser extensions for data collection and completed value surveys. The authors highlight the lack of transparency in recommendation algorithms and their impact on public opinion. X has not officially responded, but a former product lead indicated the algorithm was adjusted, reducing such recommendations by an order of magnitude.