Measuring the crowd - A preliminary taxonomy of crowdsourcing metrics

Eoin Cullina, Kieran Conboy, Lorraine Morgan

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

17 Citations (Scopus)

Abstract

Crowdsourcing initiatives benefit from tapping into diversity. A vast plethora of disparate individuals, organizations, frameworks and skillsets can all play a role in sourcing solutions to a challenge. Nevertheless, while crowdsourcing has become a pervasive phenomenon, there is a paucity of research that addresses how the crowdsourcing process is measured. Whereas research has advanced various taxonomies of crowdsourcing none to date have specifically addressed the issue of measuring either specific stages of the crowdsourcing process or the process as a whole. As a first step towards achieving this goal, this research-inprogress paper examines crowdsourcing at the operational level with a view towards (i) identifying the parts of the process (ii) identifying what can be measured and (iii) categorising operational metrics to facilitate deployment in practice. The taxonomy advanced is overarching in nature and can be deployed across disciplines. Furthermore, the preliminary taxonomy presented will offer practitioners a comprehensive list of metrics that will enable them to facilitate comparison across various crowdsourcing initiatives.

Original languageEnglish
Title of host publicationProceedings of the 11th International Symposium on Open Collaboration, OPENSYM 2015
PublisherAssociation for Computing Machinery, Inc
ISBN (Electronic)9781450336666
DOIs
Publication statusPublished - 19 Aug 2015
Externally publishedYes
Event11th International Symposium on Open Collaboration, OPENSYM 2015 - San Francisco, United States
Duration: 19 Aug 201521 Aug 2015

Publication series

NameProceedings of the 11th International Symposium on Open Collaboration, OPENSYM 2015

Conference

Conference11th International Symposium on Open Collaboration, OPENSYM 2015
Country/TerritoryUnited States
CitySan Francisco
Period19/08/1521/08/15

Keywords

  • Crowdsourcing
  • Metrics
  • Taxonomy generation

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