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The Collaboration and Communication Networks Within the Crowd

Banff International Research Station for Mathematical Innovation and Discovery

This presentation shares some of the key findings from a long term, joint research project with Mary Gray that examines workers’ experiences in crowdsourcing-for-hire labor markets. One result from 19 months of ethnographic field work, in both India and the United States across 4 different crowdsourcing platforms, is that despite the designs of crowdsourcing sites to maximize efficiencies through atomized, autonomous workflows, the most active crowdworkers are not the independent workers they are assumed to be. Instead, workers collaborate extensively to address both technical and social needs left open by the platforms they work on. Specifically, crowdworkers collaborate with members of their networks to 1) manage the administrative overhead associated with crowdwork, 2) find lucrative tasks and reputable employers and 3) recreate the social connections and support often associated with brick-and-mortar work environments. We then build on and extend this discovery by mapping the entire communication network of workers on Amazon Mechanical Turk, a leading crowdsourcing platform. We execute a task in which over 10,000 workers from across the globe self-report their communication links to other workers, thereby mapping the communication network among workers. Our results suggest that while a large percentage of workers indeed appear to be independent, there is a rich network topology over the rest of the population. That is, there is a substantial communication network within the crowd.

Mathematics; Game theory, economics, social and behavioral sciences; Computer science; Applied computer science

video/mp4

Author affiliation: Microsoft Research

2017-02-27

Attribution-NonCommercial-NoDerivatives 4.0 International

http://hdl.handle.net/2429/60734

Unreviewed

http://creativecommons.org/licenses/by-nc-nd/4.0/