Trustworthiness in Enterprise Crowdsourcing: a Taxonomy & evidence from data
Abstract
In this paper we study the trustworthiness of the crowd for crowdsourced software development. Through the study of literature from various domains, we present the risks that impact the trustworthiness in an enterprise context. We survey known techniques to mitigate these risks. We also analyze key metrics from multiple years of empirical data of actual crowdsourced software development tasks from two leading vendors. We present the metrics around untrustworthy behavior and the performance of certain mitigation techniques. Our study and results can serve as guidelines for crowdsourced enterprise software development.
Cite
@article{arxiv.1809.09477,
title = {Trustworthiness in Enterprise Crowdsourcing: a Taxonomy & evidence from data},
author = {Anurag Dwarakanath and Shrikanth N. C. and Kumar Abhinav and Alex Kass},
journal= {arXiv preprint arXiv:1809.09477},
year = {2018}
}
Comments
Author's submitted version. Final version accepted at ICSE SEIP 2016. Published version at: https://dl.acm.org/citation.cfm?id=2889225