Automatically Assessing Wikipedia Article Quality by Exploiting Article–Editor Networks

We consider the problem of automatically assessing Wikipedia article quality. We develop several models to rank articles by using the editing relations between articles and editors. First, we create a basic model by modeling the article-editor network. Then we design measures of an editor’s contribu...

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Bibliographic Details
Published inAdvances in Information Retrieval pp. 574 - 580
Main Authors Li, Xinyi, Tang, Jintao, Wang, Ting, Luo, Zhunchen, de Rijke, Maarten
Format Book Chapter
LanguageEnglish
Published Cham Springer International Publishing
SeriesLecture Notes in Computer Science
Subjects
Editing Action
Feature Article
Ranking Performance
Simple Weighted
Weighted Model
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Summary:We consider the problem of automatically assessing Wikipedia article quality. We develop several models to rank articles by using the editing relations between articles and editors. First, we create a basic model by modeling the article-editor network. Then we design measures of an editor’s contribution and build weighted models that improve the ranking performance. Finally, we use a combination of featured article information and the weighted models to obtain the best performance. We find that using manual evaluation to assist automatic evaluation is a viable solution for the article quality assessment task on Wikipedia.
ISBN:9783319163536
3319163531
ISSN:0302-9743
1611-3349
DOI:10.1007/978-3-319-16354-3_64