Matching or Crashing? Personality-based Team Formation in Crowdsourcing Environments
January 26, 2015 Β· Declared Dead Β· π arXiv.org
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Authors
Ioanna Lykourentzou, Angeliki Antoniou, Yannick Naudet
arXiv ID
1501.06313
Category
cs.HC: Human-Computer Interaction
Cross-listed
cs.CY,
cs.SI
Citations
6
Venue
arXiv.org
Last Checked
4 months ago
Abstract
"Does placing workers together based on their personality give better performance results in cooperative crowdsourcing settings, compared to non-personality based crowd team formation?" In this work we examine the impact of personality compatibility on the effectiveness of crowdsourced team work. Using a personality-based group dynamics approach, we examine two main types of personality combinations (matching and crashing) on two main types of tasks (collaborative and competitive). Our experimental results show that personality compatibility significantly affects the quality of the team's final outcome, the quality of interactions and the emotions experienced by the team members. The present study is the first to examine the effect of personality over team result in crowdsourcing settings, and it has practical implications for the better design of crowdsourced team work.
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