dc.contributor.author |
Liu, Jiamou |
en |
dc.contributor.author |
Wei, Ziheng |
en |
dc.contributor.editor |
Singh, S |
en |
dc.contributor.editor |
Markovitch, S |
en |
dc.coverage.spatial |
San Francisco, USA |
en |
dc.date.accessioned |
2018-10-16T21:00:58Z |
en |
dc.date.issued |
2017-07 |
en |
dc.identifier.citation |
Thirty-First AAAI Conference on Artificial Intelligence, San Francisco, USA, 04 Feb 2017 - 09 Feb 2017. Editors: Singh S, Markovitch S. Proceedings of the Thirty-First AAAI Conference on Artificial Intelligence, February 4-9, 2017, San Francisco, California, USA.. The AAAI Press. 1: 600-606. Jul 2017 |
en |
dc.identifier.isbn |
978-1-57735-780-3 |
en |
dc.identifier.issn |
2159-5399 |
en |
dc.identifier.uri |
http://hdl.handle.net/2292/42056 |
en |
dc.description.abstract |
In studies of social dynamics, cohesion refers to a group's tendency to stay in unity, which -- as argued in sociometry — arises from the network topology of interpersonal ties. We follow this idea and propose a game-based model of cohesion that not only relies on the social network, but also reflects individuals' social needs. In particular, our model is a type of cooperative games where players may gain popularity by strategically forming groups. A group is socially cohesive if the grand coalition is core stable. We study social cohesion in some special types of graphs and draw a link between social cohesion and a classical notion of structural cohesion by White and Harary. We then focus on the problem of deciding whether a given social network is socially cohesive and show that this problem is CoNP-complete. Nevertheless, we give two efficient heuristics for coalition structures where players enjoy high popularity and experimentally evaluate their performances. |
en |
dc.description.uri |
http://www.aaai.org/Library/AAAI/aaai17contents.php |
en |
dc.format.medium |
Online and Print |
en |
dc.publisher |
The AAAI Press |
en |
dc.relation.ispartof |
Thirty-First AAAI Conference on Artificial Intelligence |
en |
dc.relation.ispartofseries |
Proceedings of the Thirty-First AAAI Conference on Artificial Intelligence, February 4-9, 2017, San Francisco, California, USA. |
en |
dc.rights |
Items in ResearchSpace are protected by copyright, with all rights reserved, unless otherwise indicated. Previously published items are made available in accordance with the copyright policy of the publisher. |
en |
dc.rights.uri |
https://researchspace.auckland.ac.nz/docs/uoa-docs/rights.htm |
en |
dc.rights.uri |
https://aaai.org/ocs/index.php/AAAI/AAAI17/about/submissions#copyrightNotice |
en |
dc.subject |
Computational social science |
en |
dc.subject |
Social networks |
en |
dc.subject |
Coordination and collaboration |
en |
dc.subject |
Game theory |
en |
dc.subject |
Equilibrium |
en |
dc.title |
Network, Popularity and Social Cohesion: A Game-Theoretic Approach |
en |
dc.type |
Conference Item |
en |
pubs.begin-page |
600 |
en |
pubs.volume |
1 |
en |
dc.rights.holder |
Copyright: Association for the Advancement of Artificial
Intelligence |
en |
pubs.author-url |
https://aaai.org/ocs/index.php/AAAI/AAAI17/paper/view/14397 |
en |
pubs.end-page |
606 |
en |
pubs.finish-date |
2017-02-09 |
en |
pubs.publication-status |
Published |
en |
pubs.start-date |
2017-02-04 |
en |
dc.rights.accessrights |
http://purl.org/eprint/accessRights/OpenAccess |
en |
pubs.subtype |
Proceedings |
en |
pubs.elements-id |
682101 |
en |
pubs.org-id |
Science |
en |
pubs.org-id |
School of Computer Science |
en |
dc.identifier.eissn |
2374-3468 |
en |
pubs.record-created-at-source-date |
2017-10-04 |
en |
pubs.online-publication-date |
2017-02 |
en |