The 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?
[1]
Lada A. Adamic,et al.
How to search a social network
,
2005,
Soc. Networks.
[2]
John Scott.
Social Network Analysis
,
1988
.
[3]
Alex Pentland,et al.
Reality mining: sensing complex social systems
,
2006,
Personal and Ubiquitous Computing.
[4]
L. Freeman.
Centrality in social networks conceptual clarification
,
1978
.
[5]
S. Borgatti,et al.
Notions of position in social network analysis
,
1992
.
[6]
R. Hanneman.
Introduction to Social Network Methods
,
2001
.
[7]
Paul Dourish,et al.
Social and temporal structures in everyday collaboration
,
2004,
CHI.
[8]
Stanley Wasserman,et al.
Social Network Analysis: Methods and Applications
,
1994,
Structural analysis in the social sciences.
[9]
P. Bonacich.
Power and Centrality: A Family of Measures
,
1987,
American Journal of Sociology.
[10]
Elizabeth D. Mynatt,et al.
Leveraging social networks for information sharing
,
2004,
CSCW.
[11]
Stephen P. Borgatti,et al.
Centrality and network flow
,
2005,
Soc. Networks.
[12]
Dennis F. Galletta,et al.
Individual Centrality and Performance in Virtual R&D Groups: An Empirical Study
,
2003,
Manag. Sci..
[13]
Yutaka Matsuo,et al.
Real-world oriented information sharing using social networks
,
2005,
GROUP '05.
[14]
Ching-Yung Lin,et al.
Modeling and predicting personal information dissemination behavior
,
2005,
KDD '05.