What is it about?
We describe how one can spawn crowdsourcing tasks upon multiple communities of performers, thus leveraging the peculiar characteristics and capabilities of the community members. We show that dynamic adaptation of crowdsourcing campaigns to community behaviour is particularly relevant.
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Why is it important?
We demonstrate that this approach can be very effective for obtaining answers from communities, with very different sizes, precision, delay, and cost, by exploiting the social networking relations and the features of the crowdsourcing task. We show the approach at work within the CrowdSearcher platform, which allows configuring and dynamically adapting crowdsourcing campaigns tailored to different communities. We report on an experiment demonstrating the effectiveness of the approach. We demonstrate that this approach can be very effective for obtaining answers from communities, with very different sizes, precision, delay and cost, by exploiting the social networking relations and the features of the crowdsourcing task.
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This approach can be very effective for obtaining answers from communities, with very different sizes, precision, delay, and cost.
Marco Brambilla
Politecnico di Milano
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This page is a summary of: Community-based crowdsourcing, April 2014, ACM (Association for Computing Machinery),
DOI: 10.1145/2567948.2578835.
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