Bibtex export

 

@incollection{ Hannák2017,
 title = {Bias in Online Freelance Marketplaces: Evidence from TaskRabbit and Fiverr},
 author = {Hannák, Anikó and Wagner, Claudia and Garcia, David and Mislove, Alan and Strohmaier, Markus and Wilson, Christo},
 year = {2017},
 booktitle = {CSCW'17: Proceedings of the 2017 ACM Conference on Computer Supported Cooperative Work and Social Computing},
 pages = {1914-1933},
 address = {New York, NY},
 publisher = {Association for Computing Machinery (ACM)},
 isbn = {978-1-4503-4335-0},
 doi = {https://doi.org/10.1145/2998181.2998327},
 urn = {https://nbn-resolving.org/urn:nbn:de:0168-ssoar-68409-3},
 abstract = {Online freelancing marketplaces have grown quickly in recent years. In theory, these sites offer workers the ability to earn money without the obligations and potential social biases associated with traditional employment frameworks. In this paper, we study whether two prominent online freelance marketplaces - TaskRabbit and Fiverr - are impacted by racial and gender bias. From these two platforms, we collect 13,500 worker profiles and gather information about workers' gender, race, customer reviews, ratings, and positions in search rankings. In both marketplaces, we find evidence of bias: we find that gender and race are significantly correlated with worker evaluations, which could harm the employment opportunities afforded to the workers. We hope that our study fuels more research on the presence and implications of discrimination in online environments.},
 keywords = {Arbeitsvermittlung; employment service; Dienstleistung; service; Digitalisierung; digitalization; Arbeitsangebot; labor supply; Arbeitsnachfrage; job demand; freier Beruf; profession; Internet; Internet; Vorurteil; prejudice; geschlechtsspezifische Faktoren; gender-specific factors; Rassismus; racism; Diskriminierung; discrimination}}