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Conference Paper: Exploring temporal communication through social networks

TitleExploring temporal communication through social networks
Authors
Issue Date2007
Citation
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2007, v. 4662 LNCS n. PART 1, p. 10-30 How to Cite?
AbstractThe dissemination of information in social networks and the relative effect of ICT (Information and Communications Technology) use has long been an interesting area of study in the field of sociology, human computer interaction and computer supported cooperative work. To date, a lot of research has been conducted regarding an actor's mobile phone usage behavior while disseminating information within a mobile social network. In this study, we explore the structured network position of individuals using mobile phone and their ability to disseminate information within their social network. Our proposition is that an actor's ability to disseminate information within a social group is affected by their structural network position. In this paper, we determine an actor's structural network position by four different measures of centrality - (i) degree, (ii) closeness, (iii) betweenness, and (iv) eigenvector centrality. We analyse the Reality Mining dataset, which contains mobile phone usage data over a 9 month period for exploring the association between the structural positions of different actors in a temporal communication. We extract relational data to construct a social network of the mobile phone users in order to determine the association between their position in the network and their ability to disseminate information. The following questions form the basis for this study: Does information dissemination capability of an actor reflect their structural position within a social network? How do different measures of centrality associate with the information dissemination capability of an actor? Are highly central actors able to disseminate information more effectively than those who have a lower central position within a social network? © IFIP International Federation for Information Processing 2007.
Persistent Identifierhttp://hdl.handle.net/10722/194201
ISSN
2005 Impact Factor: 0.402
2015 SCImago Journal Rankings: 0.252

 

DC FieldValueLanguage
dc.contributor.authorHossain, L-
dc.contributor.authorChung, KSK-
dc.contributor.authorMurshed, STH-
dc.date.accessioned2014-01-30T03:32:18Z-
dc.date.available2014-01-30T03:32:18Z-
dc.date.issued2007-
dc.identifier.citationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2007, v. 4662 LNCS n. PART 1, p. 10-30-
dc.identifier.issn0302-9743-
dc.identifier.urihttp://hdl.handle.net/10722/194201-
dc.description.abstractThe dissemination of information in social networks and the relative effect of ICT (Information and Communications Technology) use has long been an interesting area of study in the field of sociology, human computer interaction and computer supported cooperative work. To date, a lot of research has been conducted regarding an actor's mobile phone usage behavior while disseminating information within a mobile social network. In this study, we explore the structured network position of individuals using mobile phone and their ability to disseminate information within their social network. Our proposition is that an actor's ability to disseminate information within a social group is affected by their structural network position. In this paper, we determine an actor's structural network position by four different measures of centrality - (i) degree, (ii) closeness, (iii) betweenness, and (iv) eigenvector centrality. We analyse the Reality Mining dataset, which contains mobile phone usage data over a 9 month period for exploring the association between the structural positions of different actors in a temporal communication. We extract relational data to construct a social network of the mobile phone users in order to determine the association between their position in the network and their ability to disseminate information. The following questions form the basis for this study: Does information dissemination capability of an actor reflect their structural position within a social network? How do different measures of centrality associate with the information dissemination capability of an actor? Are highly central actors able to disseminate information more effectively than those who have a lower central position within a social network? © IFIP International Federation for Information Processing 2007.-
dc.languageeng-
dc.relation.ispartofLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)-
dc.titleExploring temporal communication through social networks-
dc.typeConference_Paper-
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.scopuseid_2-s2.0-38049123045-
dc.identifier.volume4662 LNCS-
dc.identifier.issuePART 1-
dc.identifier.spage10-
dc.identifier.epage30-

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