Labeling images with a computer game
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
TANGENT: a novel, 'Surprise me', recommendation algorithm
Proceedings of the 15th ACM SIGKDD international conference on Knowledge discovery and data mining
Crowdsourcing systems on the World-Wide Web
Communications of the ACM
Enhancing credibility judgment of web search results
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Augmenting web pages and search results to support credibility assessment
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Reliability prediction of webpages in the medical domain
ECIR'12 Proceedings of the 34th European conference on Advances in Information Retrieval
Web credibility: features exploration and credibility prediction
ECIR'13 Proceedings of the 35th European conference on Advances in Information Retrieval
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The web content is the main source of information for many users. However, due to the open nature of today's web anyone can produce and publish content, which, as a result, is not always reliable. As such, mechanisms to evaluate the web content credibility are needed. In this paper, we describe CredibleWeb, a prototype crowdsourcing platform for web content evaluation with a two-fold goal: (1) to build a social enhanced and large scale dataset of credibility labeled web pages that enables the evaluation of different strategies for web credibility prediction, and (2) to investigate how various design elements are useful in engaging users to actively evaluate web pages credibility. We outline the challenges related with the design of a crowdsourcing platform for web credibility evaluation and describe our initial efforts.