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Analyzing on-boarding time in context of crowdsourcing

  • Kumar Abhinav
  • , Alex Kass
  • , Alpana Dubey
  • , Gurdeep Virdi
  • Accenture Labs
  • Accenture

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

1 Citation (Scopus)

Abstract

Crowdsourcing is an emerging area which leverages collective intelligence of the crowd. Although crowdsourcing provides several benefits, it also brings uncertainty in any project ex- ecution. The uncertainty may be because of the time taken in on-boarding workers and lack of confidence in workers. The On-boarding time specifically becomes important when tasks are of short duration as it is not worth spending too much of time in on-boarding a worker for short task. In this paper, we empirically analyze 59,597 tasks data from Up- work, an online marketplace, to understand major factors that impact On-boarding time. We identified that certain factors, such as Feedback, Hiring rate, Total hours spent, Length of requirement etc., affect the On-boarding time. We applied two predictive models to predict the On-boarding time. Our study provides insights for researchers, organizations, etc. who are looking to accomplish their tasks through crowds ourcing and helps them to better understand factors which inuence the On-boarding time.

Original languageEnglish
Title of host publicationSWAN 2016 - Proceedings of the 2nd International Workshop on Software Analytics, co-located with FSE 2016
EditorsLatifa Guerrouj, David Lo, Olga Baysal, Jacek Czerwonka, Brendan Murphy
PublisherAssociation for Computing Machinery, Inc
Pages29-35
Number of pages7
ISBN (Electronic)9781450343954
DOIs
Publication statusPublished - 13 Nov 2016
Externally publishedYes
Event2nd International Workshop on Software Analytics, SWAN 2016 - Seattle, United States
Duration: 13 Nov 2016 → …

Publication series

NameSWAN 2016 - Proceedings of the 2nd International Workshop on Software Analytics, co-located with FSE 2016

Conference

Conference2nd International Workshop on Software Analytics, SWAN 2016
Country/TerritoryUnited States
CitySeattle
Period13/11/16 → …

Keywords

  • Crowds ourcing
  • Data Analytics
  • Flash Teams

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