Not logged in.

Contribution Details

Type Working Paper
Scope Discipline-based scholarship
Title Data Analytics on Online Labor Markets: Opportunities and Challenges
Organization Unit
Authors
  • Michael Feldman
  • Frida Juldaschewa
  • Abraham Bernstein
Language
  • English
Institution Cornell University
Series Name ArXiv.org
Number 1707.01790
ISSN 2331-8422
Date 2017
Abstract Text The data-driven economy has led to a significant shortage of data scientists. To address this shortage, this study explores the prospects of outsourcing data analysis tasks to freelancers available on online labor markets (OLMs) by identifying the essential factors for this endeavor. Specifically, we explore the skills required from freelancers, collect information about the skills present on major OLMs, and identify the main hurdles for out-/crowd-sourcing data analysis. Adopting a sequential mixed-method approach, we interviewed 20 data scientists and subsequently surveyed 80 respondents from OLMs. Besides confirming the need for expected skills such as technical/mathematical capabilities, it also identifies less known ones such as domain understanding, an eye for aesthetic data visualization, good communication skills, and a natural understanding of the possibilities/limitations of data analysis in general. Finally, it elucidates obstacles for crowdsourcing like the communication overhead, knowledge gaps, quality assurance, and data confidentiality, which need to be mitigated.
Other Identification Number merlin-id:15581
PDF File Download from ZORA
Export BibTeX
EP3 XML (ZORA)