Crowdsourcing for search and data mining
ACM SIGIR Forum
Crowdsourcing for information retrieval
ACM SIGIR Forum
Towards an integrated crowdsourcing definition
Journal of Information Science
ESWC'12 Proceedings of the 9th international conference on The Semantic Web: research and applications
Quality through flow and immersion: gamifying crowdsourced relevance assessments
SIGIR '12 Proceedings of the 35th international ACM SIGIR conference on Research and development in information retrieval
Crowdsourcing for information retrieval: introduction to the special issue
Information Retrieval
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Crowdsourcing has emerged in recent years as an exciting new avenue for leveraging the tremendous potential and resources of today's digitally-connected, diverse, distributed workforce. Generally speaking, crowdsourcing describes outsourcing of tasks to a large group of people instead of assigning such tasks to an in-house employee or contractor. Crowdsourcing platforms such as Amazon Mechanical Turk and CrowdFlower have gained particular attention as active online market places for reaching and tapping into this glut of a still largely under-utilized workforce. Crowdsourcing offers intriguing new opportunities for accomplishing different kinds of tasks or achieving broader participation than previously possible, as well as completing standard tasks more accurately in less time and at lower cost. Unlocking the potential of crowdsourcing in practice, however, requires a tri-partite understanding of principles, platforms, and best practices. This tutorial will introduce the opportunities and challenges of crowdsourcing while discussing the three issues above. This will provide attendees with a basic foundation to begin applying crowdsourcing in the context of their own particular tasks.