Probabilistic Relation between Triadic Closure and the Balance of Social Networks in Presence of Influence

Probabilistic Relation between Triadic Closure and the Balance of Social Networks in Presence of Influence

Rahul Saha (Lovely Professional University, Phagwara, India), G. Geetha (Lovely Professional University, Phagwara, India) and Gulshan Kumar (Lovely Professional University, Phagwara, India)
DOI: 10.4018/IJCBPL.2015100104
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Data analysis in social networking is a major research concern in todays' environment in the field of interpretation models of data for any network. Social networking includes only two types of relationships: firstly, a friendly relation with whom one is having a link that can be considered as a positive relation and secondly, a relationship with which one is not connected or so called one's enemies labelled as negative relationships. Balanced theorem of social networking claims that all the nodes in the social network can be divided into two sets: a friendship set and an enemy set and provides the global view of relationships. In this paper, the authors have shown a probabilistic model to show that the global view of social links does not only depend on negative and positive relations to be distinguished, but it also depends on influences parameters.
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In the present world of social communication, the data analysis of social networks and identifying the human behaviour is a challenging issue. A number of researchers have done remarkable analysis on such data and have interpreted different social networking features. One of such features tell us about triadic closure. Triadic closure discussed by the authors in Wang (2012) and Huang, 2014), shown in Figure 1, highlights that if there are two nodes (users) having a common friend, there is a possibility that the two nodes will also become friends in the near future, and this often happens in our social lives. Not only social networking sites, triadic closures are also an obvious phenomenon in different social affiliations as discussed in Lattanzi and Sivakumar (2009). The reason behind this triadic closure somehow depends on the user’s behaviour and social influences.

Figure 1.

Triadic closure property


In the structure of social networks, two types of social relations or links, as described by the authors Tang (2012) and Cartwright and Harary (1956), are practically seen: Positive relation (+ve) deals with the connection between two nodes and negative relation (-ve) which includes the nodes with whom we are not having any friendship. In our further studies, we have extended the concept of negative relations as an enemy link or no connection present between two nodes to generalize the facts. Let us consider the scenario of Facebook, Twitter or any other social networking sites. We often categorize the links in our social networking sites as family, colleagues, familiar and so on. These links are positive links and those with whom we are not connected but come as a suggestion for friendship in the social networking sites can be considered as negative links. Apart from triadic closure, the data analysis shows the stability of the network structure depending upon these +ve or –ve relations. The stability of the social network is defined by the Balanced Theorem described by the authors in Heider (1946) and Heider (1958). The stability comes in the network when we can categorize the +ve and –ve links in two distinct global sets. As social network deals with building up connection among two nodes or people socially, the reasons of such connections are dynamic. Often we always talk about the term affiliation. The social affiliation factors shown by Lattanzi & Sivakumar (2009) and Borgatti and Halgin (2011) influence a lot to create a +ve link. Along with that, the users’ dynamic behaviour and different social contextual influences can also remove a link.


Previous Work

The social structural balance depending upon positive and negative relations was introduced by the author in Heider (1946) and Heider (1958). Many researchers (e.g. Yi Qian Sibel Adalı, 2014) have extended this theory to prove different features of social networks. In paper Khanafiah & Situngkir (2004) the authors have shown their analysis of social networks where multiple agents are present in the scenario. One of the most valuable researches along these lines is the classic work by Davis, Holland, and Leinhardt using the sociometric data bank, a collection of sociometric measurements of positive interpersonal sentiments from different settings to investigate the presence of structural balance, clustering, hierarchy, and transitivity as described by the authors Davis (1970), Davis and Leinhardt (1972) and Holland and Leinhardt (1971, 1973). Many researches have projected on the socio metric measurements and micro level structure (local) and macro level (global) structures have been proposed further.

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