Co-destruction Patterns in Crowdsourcing: Formal/Technical Paper
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), ISSN: 1611-3349, Vol: 12127 LNCS, Page: 54-69
2020
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Conference Paper Description
Crowdsourcing has been a successful paradigm in organising a large number of actors to work on specific tasks and contribute to knowledge collectively. However, the openness of such systems allows destructive patterns to form through actors’ dynamics. As a result, the collective effort of actors may not achieve the targeted objective due to lower engagement and lower quality contributions. There are varying forms of actor dynamics that can lead to suboptimal outcomes and this paper provides a systematic analysis of these in the form of a collection of patterns, derived from both the literature and from our own experiences with crowdsourcing systems. This collection of so-called co-destruction patterns allows for an-depth analysis of corwdsourcing systems which can benefit a comparative analysis and also assist with improvements of existing systems or the set-up of new ones. A survey reveals that these patterns have been observed in practice and are perceived as worthwhile addressing.
Bibliographic Details
http://www.scopus.com/inward/record.url?partnerID=HzOxMe3b&scp=85086224352&origin=inward; http://dx.doi.org/10.1007/978-3-030-49435-3_4; https://link.springer.com/10.1007/978-3-030-49435-3_4; https://dx.doi.org/10.1007/978-3-030-49435-3_4; https://link.springer.com/chapter/10.1007/978-3-030-49435-3_4
Springer Science and Business Media LLC
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