Crowdsourcing in China: Exploring the Work Experiences of Solo Crowdworkers and Crowdfarm Workers

Wang, Yihong; Papangelis, Konstantinos; Khan, Vassilis Javed; Lykourentzou, Ioanna; Chamberlain, Alan; Saker, Michael

Abstract

Recent research highlights the potential of crowdsourcing in China. Yet very few studies explore the workplace context and experiences of Chinese crowdworkers. Those that do, focus mainly on the work experiences of solo crowdworkers but do not deal with issues pertaining to the substantial amount of people working in 'crowdfarms'. This article addresses this gap as one of its primary concerns. Drawing on a study that involves 48 participants, our research explores, compares and contrasts the work experiences of solo crowdworkers to those of crowdfarm workers. Our findings illustrate that the work experiences and context of the solo workers and crowdfarm workers are substantially different, with regards to their motivations, the ways they engage with crowdsourcing, the tasks they work on, and the crowdsourcing platforms they utilize. Overall, our study contributes to furthering the understandings on the work experiences of crowdworkers in China.

Citation

Wang, Y., Papangelis, K., Khan, V. J., Lykourentzou, I., Chamberlain, A., & Saker, M. (2020, April). Crowdsourcing in China: Exploring the Work Experiences of Solo Crowdworkers and Crowdfarm Workers. Presented at CHI '20: CHI Conference on Human Factors in Computing Systems, Honolulu, USA

• Presentation Conference Type: Edited Proceedings
• Conference Name: CHI '20: CHI Conference on Human Factors in Computing Systems
• Start Date: Apr 25, 2020
• End Date: Apr 30, 2020
• Acceptance Date: Dec 9, 2019
• Online Publication Date: Apr 30, 2020
• Publication Date: Apr 30, 2020
• Deposit Date: Jan 13, 2020
• Publicly Available Date: May 18, 2020
• Publisher: Association for Computing Machinery (ACM)
• Peer Reviewed: Peer Reviewed
• Volume: 12
• Pages: 1-13
• Book Title: CHI '20: Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems, April 2020
• ISBN: 978-1-4503-6708-0
• DOI: https://doi.org/10.1145/3313831.3376473
• Public URL: https://nottingham-repository.worktribe.com/output/3718474
• Publisher URL: https://dl.acm.org/doi/10.1145/3313831.3376473
• Related Public URLs: https://chi2020.acm.org/