Community-based Crowdsourcing

This paper is focused on community-based crowdsourcing applications, i.e. the ability of spawning 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. We demonstrate that this approach can be very effective for obtaining answers from communities, with very different size, 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.