Wiki-worthy: collective judgment of candidate notability. Issue 8 (2nd August 2016) - Margolin, Drew B.; Goodman, Sasha; Keegan, Brian; Lin, Yu-Ru; Lazer, David
Abstract : The use of socio-technical data to predict elections is a growing research area. We argue that election prediction research suffers from under-specified theoretical models that do not properly distinguish between 'poll-like' and 'prediction market-like' mechanisms understand findings. More specifically, we argue that, in systems with strong norms and reputational feedback mechanisms, individuals have market-like incentives to bias content creation toward candidates they expect will win. We provide evidence for the merits of this approach using the creation of Wikipedia pages for candidates in the 2010 US and UK national legislative elections. We find that Wikipedia editors are more likely to create Wikipedia pages for challengers who have a better chance of defeating their incumbent opponent and that the timing of these page creations coincides with periods when collective expectations for the candidate's success are relatively high.