Task relevance and diversity as worker motivation in crowdsourcing

Document Type

Conference Proceeding

Publication Date

10-24-2018

Abstract

Task assignment is a central component in crowdsourcing. Organizational studies have shown that worker motivation in completing tasks has a direct impact on the quality of individual contributions. In this work, we examine motivation-Aware task assignment in the presence of a set of workers. We propose to model motivation as a balance between task relevance and task diversity and argue that an adaptive approach to task assignment can best capture the evolving nature of motivation. Worker motivation is observed and task assignment is revisited appropriately across iterations. We prove the problem to be NP-hard as well as MaxSNP-Hard and develop efficient approximation algorithms with provable guarantees. Our experiments with synthetic data examine the scalability of our algorithms, and our live real data experiments show that capturing motivation using relevance and diversity leads to high crowdwork quality.

Identifier

85057124544 (Scopus)

ISBN

[9781538655207]

Publication Title

Proceedings IEEE 34th International Conference on Data Engineering Icde 2018

External Full Text Location

https://doi.org/10.1109/ICDE.2018.00041

First Page

365

Last Page

376

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