Social Network for Game of Thrones

Social Network for Game of Thrones

Manvi Breja, Himanshi Bhatia, Dollie Juneja
Copyright: © 2021 |Pages: 16
DOI: 10.4018/JCIT.296252
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Abstract

Along with growing interest and use, the concept of network analysis has taken a new direction to explore data and facts to find existing patterns. The paper highlights the importance of social network analysis in analyzing and mining useful information from the data across various domains. It provides an insight into need, importance and scope of Social Network Analysis. With the use of Social networking tool like NetworkX, data is being represented in the form of graph or network which is then analyzed in a more efficient way making it easier to study the interactions between different persons in Game of thrones and establishing trends existing in a network. A comparative analysis of various centrality measures such as Degree centrality, Betweenness centrality, Closeness centrality, PageRank centrality is performed to explore the features associated to find the most important character of the series based on obtained results.
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Introduction

Introduction to SNA

Social Network Analysis (SNA) is the process of analyzing relationships that exist between social entities in terms of network and graph theory (Serrat, 2017). The structure of a network consists of social entities that are often people, social groups, organizations and communities (O’Malley & Onnela, 2017). Social network analysis involves the empirical study of how social entities interact with each other within the network. The network structure is formed using nodes which is any entity like people or individual actors or groups and edges that depicts link/interaction/relationship between nodes (Serrat, 2017). The methodical analysis of networks is commonly visualized through sociograms in which the nodes are represented as points and ties are represented as lioness which is further used to visualize various commonly used social structures including meme spread, business networks, disease transmission, sexual relationships, difficult working relationships, collaboration graphs, kinship, information circulation and friendship networks. In social network analysis two nodes are said to be related if they communicate frequently or speak in some way. A social network provides various metrics for understanding networks and the individuals and groups within them. The visual analysis of networks through graphs allows us to measure the strength of the relationships and how information flows between people, groups, communities and other social entities. Thus, social network analysis is a method that provides a best possible way to visualize entities, their patterns, connections and interactions to share and make effective utilization of their knowledge (Breja, 2017). It can generate graphical representations that reveal individuals in populations that bridge social groups.

Problems Addressed by SNA

There is an increased amount of interactions over the Internet, with the proliferation of technologies and data and so social network analysis has become increasingly relevant in recent years. To handle problems in social domains and real world, Social Networks have ushered in a multidimensional approach. It provides a new angle to problem solving decisions. Social network helps us in analyzing links between individuals; the way they are socialized. The internet imposes new questions and allows a broader perspective for SNA to find solutions to analyze similar patterns in different situations, conditions when networks gravitate around certain things like money, popularity, and advertising, identifying most connection person in network also known as influential nodes, understanding the smooth flow of information between entities, finding key people that form communities, nodes sharing common interests, visualizing the strength of bond and identify clusters inside and outside the community (Bonato et al. 2016).

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