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 | Size | Format | |
---|---|---|---|---|
Exploring_self-organisation_in_crowd_teams_2019.pdf Restricted Access | 818.15 kB | Adobe PDF | View/Open Request a copy |
Items in OAR@UM are protected by copyright, with all rights reserved, unless otherwise indicated.