@article {Margolin:2016:1369-118X:1029,
title = "Wiki-worthy: collective judgment of candidate notability",
journal = "Information, Communication and Society",
parent_itemid = "infobike://routledg/rics",
publishercode ="routledg",
year = "2016",
volume = "19",
number = "8",
publication date ="2016-08-02T00:00:00",
pages = "1029-1045",
itemtype = "ARTICLE",
issn = "1369-118X",
eissn = "1468-4462",
url = "https://www.ingentaconnect.com/content/routledg/rics/2016/00000019/00000008/art00002",
doi = "doi:10.1080/1369118X.2015.1069871",
keyword = "Wikipedia, crowdsourcing, politics, social media, communication studies, election prediction",
author = "Margolin, Drew B. and Goodman, Sasha and Keegan, Brian and Lin, Yu-Ru and 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.",
}