Open AccessDesigning for Collective Intelligence and Community Resilience on Social Networks
Author(s) -
Jon Chamberlain,
Benjamin Turpin,
Maged Ali,
Kakia Chatsiou,
Kirsty O'Callaghan
Publication year - 2021
Publication title -
human computation
Language(s) - English
Resource type - Journals
ISSN - 2330-8001
DOI - 10.15346/hc.v8i2.116
Subject(s) - casual , popularity , crowdsourcing , disengagement theory , resilience (materials science) , computer science , collective action , theme (computing) , collective intelligence , knowledge management , action (physics) , data science , psychology , social psychology , world wide web , political science , law , thermodynamics , gerontology , medicine , physics , quantum mechanics , politics
The popularity and ubiquity of social networks has enabled a new form of decentralised online collaboration: groups of users gathering around a central theme and working together to solve problems, complete tasks and develop social connections. Groups that display such `organic collaboration' have been shown to solve tasks quicker and more accurately than other methods of crowdsourcing. They can also enable community action and resilience in response to different events, from casual requests to emergency response and crisis management. However, engaging such groups through formal agencies risks disconnect and disengagement by destabilising motivational structures. This paper explores case studies of this phenomenon, reviews models of motivation that can help design systems to harness these groups and proposes a framework for lightweight engagement using existing platforms and social networks.