Social Comparisons and Contributions to Online Communities: A Field Experiment on MovieLens

Abstract

We explore the use of social comparison theory as a natural
mechanism to increase contributions to an online movie
recommendation community by investigating the effects of social
information on user behavior in an online field experiment. We
find that, after receiving behavioral information about
the median user's total number of movie ratings, users below the
median demonstrate a 530% increase in the number of monthly movie
ratings, while those above the median decrease their monthly
ratings by 62%. Movements from both ends converge towards the
median, indicating conformity towards a newly-established social
norm in a community where such a norm had been absent.
Furthermore, the social information has a more dramatic effect on
those below the median, suggesting an interaction between
conformity and competitive preferences. When given
outcome information about the average user's net benefit
score from the system, consistent with social preference theory,
users with net benefit scores above average contribute 94% of the
new updates in the database. In both treatments, we find a highly
significant Red Queen Effect.