Analysis of Saudi Arabian Social Network Using Analytic Measures and Community Detection


  • Lulwah AlSuwaidan Information Systems Department, College of Computer and Information Sciences, King Saud University, Riyadh, Saudi Arabia, Information Management Department, College of Computer and Information Sciences, Al-Imam Mohammad bin Saud Islamic University, Riyadh, Saudi Arabia
  • Mourad Ykhlef Information Systems Department, College of Computer and Information Sciences, King Saud University, Riyadh, Saudi Arabia


Social network analysis, information diffusion, social influence, social media.


Recently, Social Network Analysis has received an enormous popularity in the field of social and computer sciences. The majority of the studied problems have concentrated on research of information diffusion and social influence. The aim of this research is to analyze the Saudi Arabian social network to measure its capability for information diffusion. We are targeting Saudi Arabian social network because of its importance within Arab region. It is considered the most dominant and influence among the others. Social Network Analysis measures (degree, closeness, betweenness, and eigenvector). Community detection, on the other hand, has guaranteed its ability in identifying corresponding community depends on social properties, network structure, or influencers interests. In this article, Griven-Newman community detection algorithm has been adopted to identify the corresponding community. It has been tested and visualized using NodeXL tool. Experiment was applied on Twitter users. The communities resulted and analysis measures' results showed the suitability of the Saudi Arabian network for information diffusion. 


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How to Cite

AlSuwaidan, L., & Ykhlef, M. (2017). Analysis of Saudi Arabian Social Network Using Analytic Measures and Community Detection. International Journal of Computer (IJC), 27(1), 1–12. Retrieved from