An Evolutionary Network Analysis of Crowdsourcing Research Community

Abstract

Crowdsourcing is an approach to delegate a task to a large group of people, which then suggests their own solutions for the defined task. The objective of this study is to model and describe the structure of the crowdsourcing research community and topics from the social network analysis(SNA) point of view. By applying systematic review we found 493 crowdsourcing publications which were made by 1102 authors. We observed degreasing annual growth in terms of number of publications and authors, resulting leveling interest towards crowdsourcing among scholars. Collaboration within the diffuse crowdsourcing co-author network was tighten only slightly. The structure of author and keyword network differed significantly in term of number of components. Among 1050 co-authors we found 237 subgroups, while in the case of 1243 keywords we identified only 61 interlinked research themes including the substantially large main component which covered 84 per cent share of all keywords.