A Community Rather Than A Union: Understanding Self-Organization Phenomenon on MTurk and How It Impacts Turkers and Requesters

Citation data:

Proceedings of the 2017 CHI Conference Extended Abstracts on Human Factors in Computing Systems - CHI EA '17, Vol: Part F127655, Page: 2210-2216

Publication Year:
Captures 4
Readers 4
Citations 1
Citation Indexes 1
Wang, Xinyi; Zhu, Haiyi; Li, Yangyun; Cui, Yu; Konstan, Joseph
Association for Computing Machinery (ACM)
Computer Science
conference paper description
This paper aims to understand the self-organization phenomenon among the workers of Amazon Mechanical Turk (MTurk), a well-known crowdsourcing platform. Specifically, we explored 1) why MTurk workers self-organize into online communities (Turker communities), and 2) how the workers' self-organization impacts the requesters and 3) the workers. In the first study, we conducted a field experiment by advertising the same survey tasks on both MTurk and on Turker communities. In the second study, we interviewed two founders of the Turker communities. The results suggest that 1) workers' main motivation to participate in communities is to "find good HITs". 2) For requesters, there is no indication of differences in work quality between the tasks posted on MTurk and the ones advertised on Turker communities. 3) For workers, participation in Turker communities is associated with higher income, controlled for working hours. We also learned from the interviews about why founders built the communities and their future plans.