Exploring Temporal Communication Through Social Networks

Abstract

Abstract. 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?

Powerful Independent Directors

“…For example, connections might proxy for access to information (Freeman 1979;Freeman et al 1980;Hossain et al, 2007;Kiss and Bichler 2008). If so, degree centrality implicitly assumes that information decays completely after one degree of separation (Bolland 1988), while the closeness and eigenvector measures assume a gradual decay as degrees of separation increase.…”

A Critical Review of Centrality Measures in Social Networks

“…In addition, this article evaluates the suitability of the three CM to identify key persons in the context of "problem solving in groups". More recent contributions deal with the capability of different CM for other applications (e.g., Borgatti 2006;Hossain et al 2007;Kiss and Bichler 2008;Lee et al 2010;Gloor et al 2009). For example, Kiss and Bichler (2008) investigate the quality of different CM in terms of news dissemination in a telecommunications network.…”

“…Hossain et al (2007) consider a similar issue by evaluating real-world data from the mobile sector as regards the four CM DC, CC, BC, and EC in order to assess the relationship between the centrality of an actor and his possibilities for disseminating information. It turns out that only by combining different CM the most important actors for the dissemination of information can be identified.…”

Social similarity as a driver for selfish, cooperative and altruistic behavior

“…[14] studies the impact of different "levels of altruism" of nodes involved in the dissemination process. In a more abstract setting, the effect that a node's relational position in the group has on content dissemination has been considered in [4]. The importance of designing socially-aware opportunistic networks is also demonstrated in [2], [5], [7].…”