Comparing Generic and Community-Situated Crowdsourcing for Data Validation in the Context of Recovery from Substance Use Disorders
Comparing Generic and Community-Situated Crowdsourcing for Data Validation in the Context of Recovery from Substance Use Disorders
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药物使用障碍康复背景下比较通用众包和社区众包的数据验证
DOI:
10.1145/3411764.3445399
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发表时间:
2021
期刊:
影响因子:
--
通讯作者:
Yarosh, Svetlana
中科院分区:
文献类型:
--
作者:
Rubya, Sabirat;Numainville, Joseph;Yarosh, Svetlana
Targeting the right group of workers for crowdsourcing often achieves better quality results. One unique example of targeted crowdsourcing is seeking community-situated workers whose familiarity with the background and the norms of a particular group can help produce better outcome or accuracy. These community-situated crowd workers can be recruited in different ways from generic online crowdsourcing platforms or from online recovery communities. We evaluate three different approaches to recruit generic and community-situated crowd in terms of the time and the cost of recruitment, and the accuracy of task completion. We consider the context of Alcoholics Anonymous (AA), the largest peer support group for recovering alcoholics, and the task of identifying and validating AA meeting information. We discuss the benefits and trade-offs of recruiting paid vs. unpaid community-situated workers and provide implications for future research in the recovery context and relevant domains of HCI, and for the design of crowdsourcing ICT systems.
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DOI:
10.1145/3281449
发表时间:
2018
期刊:
ACM Transactions on Social Computing
影响因子:
--
作者:
Jan, Steve T.;Wang, Chun;Zhang, Qing;Wang, Gang
通讯作者:
Wang, Gang
DOI:
--
发表时间:
2013
期刊:
Conference on Computer Supported Cooperative Work
影响因子:
--
作者:
Erin L. Brady;Yu Zhong;M. Morris;Jeffrey P. Bigham
通讯作者:
Jeffrey P. Bigham
DOI:
--
发表时间:
2011
期刊:
影响因子:
--
作者:
Nicolas Kaufmann;Thimo Schulze
通讯作者:
Thimo Schulze
影响因子:
6.3
作者:
J. Martins;J. Carilho;O. Schnell;Carlos Duarte;Francisco M. Couto;L. Carriço;Tiago Guerreiro
通讯作者:
Tiago Guerreiro
DOI:
--
发表时间:
2016
期刊:
International Database Engineering and Applications Symposium
影响因子:
--
作者:
R. M. Borromeo;Thomas Laurent;Motomichi Toyama
通讯作者:
Motomichi Toyama