inis 20(23): e2

Research Article

SAM Centrality: a Hop-Based Centrality Measure for Ranking Users in Social Network

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  • @ARTICLE{10.4108/eai.13-7-2018.163985,
        author={Abdul Samad and Mamoona Qadir and Ishrat Nawaz and Muhammad Arshad Islam and Muhammad Aleem},
        title={SAM Centrality: a Hop-Based Centrality Measure for Ranking Users in Social Network},
        journal={EAI Endorsed Transactions on Industrial Networks and Intelligent Systems},
        volume={7},
        number={23},
        publisher={EAI},
        journal_a={INIS},
        year={2020},
        month={4},
        keywords={Centrality, Social Network Analysis, Ranking, Influential User},
        doi={10.4108/eai.13-7-2018.163985}
    }
    
  • Abdul Samad
    Mamoona Qadir
    Ishrat Nawaz
    Muhammad Arshad Islam
    Muhammad Aleem
    Year: 2020
    SAM Centrality: a Hop-Based Centrality Measure for Ranking Users in Social Network
    INIS
    EAI
    DOI: 10.4108/eai.13-7-2018.163985
Abdul Samad1,*, Mamoona Qadir2, Ishrat Nawaz3, Muhammad Arshad Islam4, Muhammad Aleem4
  • 1: Capital University of Science and Technology, Islamabad Pakistan
  • 2: Khwaja Fareed University of Engineering and Information Technology, Rahim Yar Khan Pakistan
  • 3: The Islamia University of Bahawalpur, Bahawalpur Pakistan
  • 4: FAST-National University of Computer and Emerging Sciences, Islamabad Pakistan
*Contact email: writetosamadalvi@gmail.com

Abstract

Majority of researcher are attracted by the social network analysis due to the rush of people towards social network. Along with many problems, social network analysis is facing an interesting problem that is ranking of users in social network which is gaining more attention due to the increasing number of social users. Measuring centrality of nodes in a social graph, have been important issue in social network analysis. Lot of centrality methods have been proposed in this regard. In this paper, hop based centrality measures called SAM is purposed. To investigate the measure, we applied on various dataset. In comparisons, on all these social graphs, we obtain better results than other centrality measures (i.e., Degree, PageRank, Betweeness and Closeness) using SIR model.