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Cognos: Crowdsourcing Search for Topic Experts in Microblogs
| Citations: | 21 - 5 self |
BibTeX
@MISC{Ghosh_cognos:crowdsourcing,
author = {Saptarshi Ghosh and Niloy Ganguly and Naveen Sharma and Krishna P. Gummadi and Fabricio Benevenuto},
title = {Cognos: Crowdsourcing Search for Topic Experts in Microblogs},
year = {}
}
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Abstract
Finding topic experts on microblogging sites with millions of users, such as Twitter, is a hard and challenging problem. In this paper, we propose and investigate a new methodology for discovering topic experts in the popular Twitter social network. Our methodology relies on the wisdom of the Twitter crowds – it leverages Twitter Lists, which are often carefully curated by individual users to include experts on topics that interest them and whose meta-data (List names and descriptions) provides valuable semantic cues to the experts’ domain of expertise. We mined List information to build Cognos, a system for finding topic experts in Twitter. Detailed experimental evaluation based on a real-world deployment shows that: (a) Cognos infers a user’s expertise more accurately and comprehensively than state-of-the-art systems that rely on the user’s bio or tweet content, (b) Cognos scales well due to built-in mechanisms to efficiently update its experts ’ database with new users, and (c) Despite relying only on a single feature, namely crowdsourced Lists, Cognos yields results comparable to, if not better than, those given by the official Twitter experts search engine for a wide range of queries in user tests. Our study highlights Lists as a potentially valuable source of information for future content or expert search systems in Twitter.
Keyphrases
topic expert crowdsourcing search user expertise crowdsourced list user bio detailed experimental evaluation list information methodology relies wide range twitter crowd study highlight future content twitter list expert search system tweet content state-of-the-art system popular twitter social network cognos yield result expert database individual user valuable source expert domain new methodology official twitter expert single feature built-in mechanism user test real-world deployment valuable semantic cue new user
