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2014 | OriginalPaper | Buchkapitel

An Improved Social Network Analysis Method for Social Networks

verfasst von : Jongsoo Sohn, Daehyun Kang, Hansaem Park, Bok-Gyu Joo, In-Jeong Chung

Erschienen in: Advanced Technologies, Embedded and Multimedia for Human-centric Computing

Verlag: Springer Netherlands

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Abstract

Recently, Social Network Service (SNS) users are rapidly increasing, and Social Network Analysis (SNA) methods are used to analyze the structure of user relationship or messages in many fields. However, the SNA methods based on the shortest distance among nodes is time-consuming in measuring computation time. In order to solve this problem, we present a heuristic method for the shortest path search using SNS user graphs. Our proposed method consists of three steps. First, it sets a start node and a goal node in the Social Network (SN), which is represented by trees. Second, the goal node sets a temporary node starting from a skewed tree, if there is a goal node on a leaf node of the skewed tree. Finally, the betweenness and closeness centralities are computed with the heuristic shortest path search. For verification of the proposed method, we demonstrate an experimental analysis of betweenness centrality and closeness centrality, with 164,910 real data in an SNS. In the experimental results, the method shows that the computation time of betweenness centrality and closeness centrality is faster than the traditional method. This heuristic method can be used to analyze social phenomena and trends in many fields.

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Metadaten
Titel
An Improved Social Network Analysis Method for Social Networks
verfasst von
Jongsoo Sohn
Daehyun Kang
Hansaem Park
Bok-Gyu Joo
In-Jeong Chung
Copyright-Jahr
2014
Verlag
Springer Netherlands
DOI
https://doi.org/10.1007/978-94-007-7262-5_13

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