  Many online communities present user-contributed responses such as reviews of
products and answers to questions. User-provided helpfulness votes can
highlight the most useful responses, but voting is a social process that can
gain momentum based on the popularity of responses and the polarity of existing
votes. We propose the Chinese Voting Process (CVP) which models the evolution
of helpfulness votes as a self-reinforcing process dependent on position and
presentation biases. We evaluate this model on Amazon product reviews and more
than 80 StackExchange forums, measuring the intrinsic quality of individual
responses and behavioral coefficients of different communities.
