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New centrality measure for nodes based on user social status and behavior on Facebook


Forouzandeh, S and Sheikhahmadi, A and Rezaei Aghdam, A and Xu, S, New centrality measure for nodes based on user social status and behavior on Facebook, International Journal of Web Information Systems, 14, (2) pp. 158-176. ISSN 1744-0084 (2018) [Refereed Article]

Copyright Statement

Copyright 2018 Emerald Publishing Limited

DOI: doi:10.1108/IJWIS-07-2017-0053


Purpose: This paper aims to analyze the role of influential nodes on other users on Facebook social media sites by social and behavioral characteristics of users. Hence, a new centrality for user is defined, applying susceptible-infected recovered (SIR) model to identify influence of users. Results show that the combination of behavioral and social characteristics would be determined the most influential users that influence majority of nodes on social networks.

Design/methodology/approach: In this paper, the authors define a new centrality for users, considering node status and behaviors. Thus, this node has a high level of influence. Node social status includes node degree, clustering coefficient and average neighbors' node, and social status of node refers to user activities on Facebook social media website such as sending posts and receiving likes from other users. According to social status and user activity, the new centrality is defined. Finally, through the SIR model, the authors explore infection power of nodes and their influences of other node in the network.

Findings: Results show that the proposed centrality is more effective than other centrality approaches, infecting more nodes in social network. Another significant point in this research is that users who have high social status and activities on Facebook are more influential than users who have only high social status on the Facebook social media.

Originality/value: The influence of user on others in social media includes two key factors. The first factor is user social status such as node degree and clustering coefficient in social media graph and the second factor is related to user social activities in social media sites. Most centralities focused on node social status without considering node behavior. This paper analyzes the role of influential nodes on other users on Facebook social media site by social and behavioral characteristics of users.

Item Details

Item Type:Refereed Article
Keywords:social networks, social influence, node centrality, susceptible-infected recovered
Research Division:Information and Computing Sciences
Research Group:Distributed computing and systems software
Research Field:Networking and communications
Objective Division:Information and Communication Services
Objective Group:Information services
Objective Field:Electronic information storage and retrieval services
UTAS Author:Xu, S (Dr Shuxiang Xu)
ID Code:129055
Year Published:2018
Web of Science® Times Cited:5
Deposited By:Information and Communication Technology
Deposited On:2018-11-06
Last Modified:2019-07-26

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