most citedTurkScanner: Predicting the Hourly Wage of Microtasks

33 citations · 36 across the 2 of their papers we have counts for

collaborators

5 papers

cs.HC201933 cited

TurkScanner: Predicting the Hourly Wage of Microtasks

Susumu Saito, Chun-Wei Chiang, Saiph Savage +3

Workers in crowd markets struggle to earn a living. One reason for this is that it is difficult for workers to accurately gauge the hourly wages of microtasks, and they consequentl…

cs.HC20193 cited

Crowd Work on a CV? Understanding How AMT Fits into Turkers' Career Goals and Professional Profiles

Anna Kasunic, Chun-Wei Chiang, Geoff Kaufman +1

In 2013, scholars laid out a framework for a sustainable, ethical future of crowd work, recommending career ladders so that crowd work can lead to career advancement and more econo…

cs.HC2018

Crowd Coach: Peer Coaching for Crowd Workers' Skill Growth

Chun-Wei Chiang, Anna Kasunic, Saiph Savage

Traditional employment usually provides mechanisms for workers to improve their skills to access better opportunities. However, crowd work platforms like Amazon Mechanical Turk (AM…

cs.HC2018

Blockchain for Trustful Collaborations between Immigrants and Governments

Chun-Wei Chiang, Eber Betanzos, Saiph Savage

Immigrants usually are pro-social towards their hometowns and try to improve them. However, the lack of trust in their government can drive immigrants to work individually. As a re…

cs.HC2018

Understanding Interface Design and Mobile Money Perceptions in Latin America

Chun-Wei Chiang, Caroline Anderson, Claudia Flores-Saviaga +6

Mobile money can facilitate financial inclusion in developing countries, which usually have high mobile phone use and steady remittance activity. Many countries in Latin America me…