This paper presents a study of user voting on three websites: Imdb, Amazon
and BookCrossings. It reports on an expert evaluation of the voting mechanisms
of each website and a quantitative data analysis of users' aggregate voting
behavior. The results suggest that voting follows different patterns across the
websites, with higher barrier to vote introducing a more of one-off voters and
attracting mostly experts. The results also show that that one-off voters tend
to vote on popular items, while experts mostly vote for obscure, low-rated
items. The study concludes with design suggestions to address the "wisdom of
the crowd" bias.