IR evaluation methods for retrieving highly relevant documents
SIGIR '00 Proceedings of the 23rd annual international ACM SIGIR conference on Research and development in information retrieval
A tutorial on support vector regression
Statistics and Computing
He says, she says: conflict and coordination in Wikipedia
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
A content-driven reputation system for the wikipedia
Proceedings of the 16th international conference on World Wide Web
Measuring Qualities of Articles Contributed by Online Communities
WI '06 Proceedings of the 2006 IEEE/WIC/ACM International Conference on Web Intelligence
Identifying Document Topics Using the Wikipedia Category Network
WI '06 Proceedings of the 2006 IEEE/WIC/ACM International Conference on Web Intelligence
Measuring article quality in wikipedia: models and evaluation
Proceedings of the sixteenth ACM conference on Conference on information and knowledge management
Computing trust from revision history
Proceedings of the 2006 International Conference on Privacy, Security and Trust: Bridge the Gap Between PST Technologies and Business Services
Supporting Judgment of Fact Trustworthiness Considering Temporal and Sentimental Aspects
WISE '08 Proceedings of the 9th international conference on Web Information Systems Engineering
Network analysis of collaboration structure in Wikipedia
Proceedings of the 18th international conference on World wide web
Is Wikipedia growing a longer tail?
Proceedings of the ACM 2009 international conference on Supporting group work
A jury of your peers: quality, experience and ownership in Wikipedia
Proceedings of the 5th International Symposium on Wikis and Open Collaboration
Detecting Wikipedia vandalism with active learning and statistical language models
Proceedings of the 4th workshop on Information credibility
Do Wikipedians follow domain experts?: a domain-specific study on Wikipedia knowledge building
Proceedings of the 10th annual joint conference on Digital libraries
A game-theoretic model of metaphorical bargaining
ACL '10 Proceedings of the 48th Annual Meeting of the Association for Computational Linguistics
Towards identifying arguments in Wikipedia pages
Proceedings of the 20th international conference companion on World wide web
Enhancing credibility judgment of web search results
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
ImageAlert: credibility analysis of text-image pairs on the web
Proceedings of the 2011 ACM Symposium on Applied Computing
Clash of the typings: finding controversies and children's topics within queries
ECIR'11 Proceedings of the 33rd European conference on Advances in information retrieval
Mining direct antagonistic communities in explicit trust networks
Proceedings of the 20th ACM international conference on Information and knowledge management
Identifying controversial issues and their sub-topics in news articles
PAISI'10 Proceedings of the 2010 Pacific Asia conference on Intelligence and Security Informatics
Leveraging editor collaboration patterns in wikipedia
Proceedings of the 23rd ACM conference on Hypertext and social media
Identifying controversial articles in Wikipedia: a comparative study
Proceedings of the Eighth Annual International Symposium on Wikis and Open Collaboration
Mining direct antagonistic communities in signed social networks
Information Processing and Management: an International Journal
DIGTOBI: a recommendation system for Digg articles using probabilistic modeling
Proceedings of the 22nd international conference on World Wide Web
Proceedings of the 22nd ACM international conference on Conference on information & knowledge management
Towards a diversity-minded Wikipedia
Proceedings of the 3rd International Web Science Conference
Analyzing, Detecting, and Exploiting Sentiment in Web Queries
ACM Transactions on the Web (TWEB)
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Wikipedia 1 is a very large and successful Web 2.0 example. As the number of Wikipedia articles and contributors grows at a very fast pace, there are also increasing disputes occurring among the contributors. Disputes often happen in articles with controversial content. They also occur frequently among contributors who are "aggressive" or controversial in their personalities. In this paper, we aim to identify controversial articles in Wikipedia. We propose three models, namely the Basic model and two Controversy Rank (CR) models. These models draw clues from collaboration and edit history instead of interpreting the actual articles or edited content. While the Basic model only considers the amount of disputes within an article, the two Controversy Rank models extend the former by considering the relationships between articles and contributors. We also derived enhanced versions of these models by considering the age of articles. Our experiments on a collection of 19,456 Wikipedia articles shows that the Controversy Rank models can more effectively determine controversial articles compared to the Basic and other baseline models