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It’s not in their tweets: Modeling topical expertise of twitter users (2012)
| Venue: | In SocialCom/PASSAT |
| Citations: | 12 - 1 self |
BibTeX
@INPROCEEDINGS{Wagner12it’snot,
author = {Claudia Wagner and Vera Liao and Peter Pirolli and Les Nelson and Markus Strohmaier},
title = {It’s not in their tweets: Modeling topical expertise of twitter users},
booktitle = {In SocialCom/PASSAT},
year = {2012},
pages = {91--100}
}
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Abstract
Abstract—One of the key challenges for users of social media is judging the topical expertise of other users in order to select trustful information sources about specific topics and to judge credibility of content produced by others. In this paper, we explore the usefulness of different types of user-related data for making sense about the topical expertise of Twitter users. Types of user-related data include messages a user authored or re-published, biographical information a user published on his/her profile page and information about user lists to which a user belongs. We conducted a user study that explores how useful different types of data are for informing human’s expertise judgements. We then used topic modeling based on different types of data to build and assess computational expertise models of Twitter users. We use Wefollow directories as a proxy measurement for perceived expertise in this assessment. Our findings show that different types of user-related data indeed differ substantially in their ability to inform computational expertise models and humans’s expertise judgements. Tweets and retweets — which are often used in literature for gauging the expertise area of users — are surprisingly useless for inferring the expertise topics of their authors and are outperformed by other types of user-related data such as information about users’ list memberships. Our results have implications for algorithms, user interfaces and methods that focus on capturing expertise of social media users. Index Terms—expertise, user profiling, expert search, Twitter, microblogs I.
Keyphrases
twitter user user-related data modeling topical expertise different type computational expertise model topical expertise profile page specific topic social medium social medium user expertise topic biographical information expert search useful different type user list proxy measurement user interface perceived expertise index term expertise human expertise judgement key challenge user list membership expertise judgement trustful information source user belongs wefollow directory user profiling expertise area user study
