TY - GEN
T1 - MicroLapse
T2 - 22nd ACM Conference on Computer-Supported Cooperative Work and Social Computing, CSCW 2019
AU - Saito, Susumu
AU - Nakano, Teppei
AU - Kobayashi, Tetsunori
AU - Bigham, Jefrey P.
N1 - Publisher Copyright:
© 2019 Copyright held by the owner/author(s).
PY - 2019/11/9
Y1 - 2019/11/9
N2 - Working time estimation is known to be helpful for allowing crowd workers to select lucrative microtasks. We previously proposed a machine learning method for estimating the working times of microtasks, but a practical evaluation was not possible because it was unclear what errors would be problematic for workers across diferent scales of microtask working times. In this study, we formulate MicroLapse, a function that expresses a maximal error in working time prediction that workers can accept for a given working time length. We collected 60, 760 survey answers from 660 Amazon Mechanical Turk workers to formulate MicroLapse. Our evaluation of our previous method based on MicroLapse demonstrated that our working time prediction method was fairly successful for shorter microtasks, which could not have been concluded in our previous paper.
AB - Working time estimation is known to be helpful for allowing crowd workers to select lucrative microtasks. We previously proposed a machine learning method for estimating the working times of microtasks, but a practical evaluation was not possible because it was unclear what errors would be problematic for workers across diferent scales of microtask working times. In this study, we formulate MicroLapse, a function that expresses a maximal error in working time prediction that workers can accept for a given working time length. We collected 60, 760 survey answers from 660 Amazon Mechanical Turk workers to formulate MicroLapse. Our evaluation of our previous method based on MicroLapse demonstrated that our working time prediction method was fairly successful for shorter microtasks, which could not have been concluded in our previous paper.
UR - http://www.scopus.com/inward/record.url?scp=85076108359&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85076108359&partnerID=8YFLogxK
U2 - 10.1145/3311957.3359466
DO - 10.1145/3311957.3359466
M3 - Conference contribution
AN - SCOPUS:85076108359
T3 - Proceedings of the ACM Conference on Computer Supported Cooperative Work, CSCW
SP - 352
EP - 356
BT - CSCW 2019 Companion - Conference Companion Publication of the 2019 Computer Supported Cooperative Work and Social Computing
PB - Association for Computing Machinery
Y2 - 9 November 2019 through 13 November 2019
ER -