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

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.