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  1. Proceedings of the 3rd international workshop on Search and mining user-generated contents (SMUC '11)
  2. Characterizing Wikipedia pages using edit network motif profiles
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The challenge of understanding the flow of sentiments in social media documents
Trend-based and reputation-versed personalized news network
Improved answer ranking in social question-answering portals
Analysis of communities in social media
Predicting age and gender in online social networks
"I'm eating a sandwich in Glasgow": modeling locations with tweets
A comparative evaluation of personality estimation algorithms for the twin recommender system
Detection of near-duplicate user generated contents: the SMS spam collection
Characterizing Wikipedia pages using edit network motif profiles
Mining tweets for tag recommendation on social media
Mining tag similarity in folksonomies
ThemeCrowds: multiresolution summaries of twitter usage
On the generation of rich content metadata from social media

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Characterizing Wikipedia pages using edit network motif profiles

Content Provider ACM Digital Library
Author Wu, Guangyu Cunningham, Pádraig Harrigan, Martin
Abstract Good Wikipedia articles are authoritative sources due to the collaboration of a number of knowledgeable contributors. This is the many eyes idea. The edit network associated with a Wikipedia article can tell us something about its quality or authoritativeness. In this paper we explore the hypothesis that the characteristics of this edit network are predictive of the quality of the corresponding article's content. We characterize the edit network using a profile of network motifs and we show that this network motif profile is predictive of the Wikipedia quality classes assigned to articles by Wikipedia editors. We further show that the network motif profile can identify outlier articles particularly in the 'Featured Article' class, the highest Wikipedia quality class.
Starting Page 45
Ending Page 52
Page Count 8
File Format PDF
ISBN 9781450309493
DOI 10.1145/2065023.2065036
Language English
Publisher Association for Computing Machinery (ACM)
Publisher Date 2011-10-28
Publisher Place New York
Access Restriction Subscribed
Subject Keyword Authoritativeness Wikipedia Network motifs
Content Type Text
Resource Type Article
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