TurkScanner: Predicting the hourly wage of microtasks

Susumu Saito, Teppei Nakano, Chun Wei Chiang, Tetsunori Kobayashi, Saiph Savage, Jeffrey P. Bigham

研究成果: Conference contribution

6 被引用数 (Scopus)

抄録

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 consequently end up performing labor with little pay. In general, workers are provided with little information about tasks, and are left to rely on noisy signals, such as textual description of the task or rating of the requester. This study explores various computational methods for predicting the working times (and thus hourly wages) required for tasks based on data collected from other workers completing crowd work. We provide the following contributions. (i) A data collection method for gathering real-world training data on crowd-work tasks and the times required for workers to complete them; (ii) TurkScanner: a machine learning approach that predicts the necessary working time to complete a task (and can thus implicitly provide the expected hourly wage). We collected 9,155 data records using a web browser extension installed by 84 Amazon Mechanical Turk workers, and explored the challenge of accurately recording working times both automatically and by asking workers. TurkScanner was created using ∼150 derived features, and was able to predict the hourly wages of 69.6% of all the tested microtasks within a 75% error. Directions for future research include observing the effects of tools on people's working practices, adapting this approach to a requester tool for better price setting, and predicting other elements of work (e.g., the acceptance likelihood and worker task preferences).

本文言語English
ホスト出版物のタイトルThe Web Conference 2019 - Proceedings of the World Wide Web Conference, WWW 2019
出版社Association for Computing Machinery, Inc
ページ3187-3193
ページ数7
ISBN(電子版)9781450366748
DOI
出版ステータスPublished - 2019 5月 13
イベント2019 World Wide Web Conference, WWW 2019 - San Francisco, United States
継続期間: 2019 5月 132019 5月 17

出版物シリーズ

名前The Web Conference 2019 - Proceedings of the World Wide Web Conference, WWW 2019

Conference

Conference2019 World Wide Web Conference, WWW 2019
国/地域United States
CitySan Francisco
Period19/5/1319/5/17

ASJC Scopus subject areas

  • コンピュータ ネットワークおよび通信
  • ソフトウェア

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