Paper Info
Title
Automatic quality assessment of content created collaboratively by web communities: a case study of wikipedia
Abstract
The old dream of a universal repository containing all the human knowledge and culture is becoming possible through the Internet and the Web. Moreover, this is happening with the direct collaborative, participation of people. Wikipedia is a great example. It is an enormous repository of information with free access and edition, created by the community in a collaborative manner. However, this large amount of information, made available democratically and virtually without any control, raises questions about its relative quality. In this work we explore a significant number of quality indicators, some of them proposed by us and used here for the first time, and study their capability to assess the quality of Wikipedia articles. Furthermore, we explore machine learning techniques to combine these quality indicators into one single assessment judgment. Through experiments, we show that the most important quality indicators are the easiest ones to extract, namely, textual features related to length, structure and style. We were also able to determine which indicators did not contribute significantly to the quality assessment. These were, coincidentally, the most complex features, such as those based on link analysis. Finally, we compare our combination method with state-of-the-art solution and show significant improvements in terms of effective quality prediction.
Year
DOI
Venue
2009
10.1145/1555400.1555449
JCDL
Keywords
Field
DocType
collaborative manner,important quality indicator,quality indicator,effective quality prediction,relative quality,wikipedia article,automatic quality assessment,significant improvement,case study,direct collaborative,quality assessment,web community,enormous repository,svm,machine learning,wikipedia,link analysis
Data science,World Wide Web,Link analysis,Computer science,Support vector machine,Human knowledge,The Internet
Conference
ISSN
Citations 
PageRank 
2575-7865
47
2.13
References 
Authors
14
4
Name
Order
Citations
PageRank
Daniel Hasan Dalip114011.56
Marcos André Gonçalves22740191.03
Marco Cristo361839.30
Pável Calado480955.33