Labeling images with a computer game
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
World explorer: visualizing aggregate data from unstructured text in geo-referenced collections
Proceedings of the 7th ACM/IEEE-CS joint conference on Digital libraries
Can social annotation support users in evaluating the trustworthiness of video clips?
Proceedings of the 2nd ACM workshop on Information credibility on the web
A report on the human computation workshop (HComp 2009)
ACM SIGKDD Explorations Newsletter
Crowdsourcing systems on the World-Wide Web
Communications of the ACM
Human computation: a survey and taxonomy of a growing field
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
ACM multimedia 2013 workshop on crowdsourcing for multimedia
Proceedings of the 21st ACM international conference on Multimedia
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Crowdsourcing for multimedia involves exploiting both human intelligence and the combination of a large number of individual human contributions (i.e., the 'wisdom of the crowd') to develop techniques, systems and data sets that advance the state of the art. The ACM Multimedia 2012 Workshop on Crowdsourcing for Multimedia (CrowdMM 2012) provides a forum presenting crowdsourcing techniques for multimedia, as well as innovative ideas exemplifying how multimedia research can benefit from crowdsourcing. Through presented papers, invited talks and a panel, the workshop will promote interactive discussion on the scope and research potentials of crowdsourcing. The goal is to provide information to the multimedia research community on the principles of crowdsourcing and to inspire researchers to address the limitations of current studies by innovative use of human computation and collective intelligence. The workshop views crowdsourcing in the broad sense: it encompasses both unsolicited human contributions, e.g., tags assigned by users to images, and also solicited contributions, e.g., annotations gathered by making use of crowdsourcing platforms that micro-outsource tasks to a large pool of human workers.