Open Access

ARTICLE

Complex Network Formation and Analysis of Online Social Media Systems

Hafiz Abid Mahmood Malik^*

Faculty of Computer Studies, Arab Open University, A’ali, Kingdom of Bahrain

* Corresponding Author:Hafiz Abid Mahmood Malik. Email:

(This article belongs to the Special Issue: Application of Computer Modeling and Simulation in Social Complex System)

Computer Modeling in Engineering & Sciences 2022, 130(3), 1737-1750. https://doi.org/10.32604/cmes.2022.018015

Received 23 June 2021; Accepted 10 September 2021; Issue published 30 December 2021

Abstract

To discover and identify the influential nodes in any complex network has been an important issue. It is a significant factor in order to control over the network. Through control on a network, any information can be spread and stopped in a short span of time. Both targets can be achieved, since network of information can be extended and as well destroyed. So, information spread and community formation have become one of the most crucial issues in the world of SNA (Social Network Analysis). In this work, the complex network of twitter social network has been formalized and results are analyzed. For this purpose, different network metrics have been utilized. Visualization of the network is provided in its original form and then filter out (different percentages) from the network to eliminate the less impacting nodes and edges for better analysis. This network is analyzed according to different centrality measures, like edge-betweenness, betweenness centrality, closeness centrality and eigenvector centrality. Influential nodes are detected and their impact is observed on the network. The communities are analyzed in terms of network coverage considering the Minimum Spanning Tree, shortest path distribution and network diameter. It is found that these are the very effective ways to find influential and central nodes from such big social networks like Facebook, Instagram, Twitter, LinkedIn, etc.

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Keywords

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