Please use this identifier to cite or link to this item: https://www.um.edu.mt/library/oar/handle/123456789/102258
Title: Exploring self-organisation in crowd teams
Authors: Lykourentzou, Ioanna
Liapis, Antonios
Papastathis, Costas
Papangelis, Konstantinos
Vassilakis, Costas
Keywords: Collective behavior
Artificial intelligence
Human-computer interaction
Crowds
Issue Date: 2019
Publisher: Springer
Citation: Lykourentzou, I., Liapis, A., Papastathis, C., Papangelis, K. & Vassilakis, C. (2019). Exploring self-organisation in crowd teams. I3E 2019: Digital Transformation for a Sustainable Society in the 21st Century, Trondheim. 164-175.
Abstract: Online crowds have the potential to do more complex work in teams, rather than as individuals. Team formation algorithms typically maximize some notion of global utility of team output by allocating people to teams or tasks. However, decisions made by these algorithms do not consider the decisions or preferences of the people themselves. This paper explores a complementary strategy, which relies on the crowd itself to self-organize into effective teams. Our preliminary results show that users perceive the ability to choose their teammate extremely useful in a crowdsourcing setting. We also find that self-organisation makes users feel more productive, creative and responsible for their work product.
URI: https://www.um.edu.mt/library/oar/handle/123456789/102258
Appears in Collections:Scholarly Works - InsDG

Files in This Item:
File Description SizeFormat 
Exploring_self-organisation_in_crowd_teams_2019.pdf
  Restricted Access
818.15 kBAdobe PDFView/Open Request a copy


Items in OAR@UM are protected by copyright, with all rights reserved, unless otherwise indicated.