Item-based collaborative filtering recommendation algorithms
Proceedings of the 10th international conference on World Wide Web
Studying cooperation and conflict between authors with history flow visualizations
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Feature-rich part-of-speech tagging with a cyclic dependency network
NAACL '03 Proceedings of the 2003 Conference of the North American Chapter of the Association for Computational Linguistics on Human Language Technology - Volume 1
Measuring Qualities of Articles Contributed by Online Communities
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
Size matters: word count as a measure of quality on wikipedia
Proceedings of the 17th international conference on World Wide Web
Automatic scoring of online discussion posts
Proceedings of the 2nd ACM workshop on Information credibility on the web
On the credibility of wikipedia: an accessibility perspective
Proceedings of the 2nd ACM workshop on Information credibility on the web
A "quick and dirty" website data quality indicator
Proceedings of the 2nd ACM workshop on Information credibility on the web
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
Blog credibility ranking by exploiting verified content
Proceedings of the 3rd workshop on Information credibility on the web
Automatically assessing the post quality in online discussions on software
ACL '07 Proceedings of the 45th Annual Meeting of the ACL on Interactive Poster and Demonstration Sessions
Incremental collaborative filtering for highly-scalable recommendation algorithms
ISMIS'05 Proceedings of the 15th international conference on Foundations of Intelligent Systems
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User generated content has been growing tremendously in recent years. This content reflects the interests and the diversity of online users. In turn, the diversity among internet users is also reflected in the quality of the content being published online. This increases the need to develop means to gauge the support available for content posted online. In this work, we aim to make use of the web-content to calculate a statistical support score for textual documents. In the proposed algorithm, phrases representing key facts are extracted to construct basic elements of the document. Search is used thereon to validate the support available for these elements online, leading to assigning an overall score for each document. Experimental results have shown a difference between the score distribution of factual news data and false facts data. This indicates that the approach seems to be a promising seed for distinguishing different articles based on the content.