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

Lulwah AlSuwaidan, Mourad Ykhlef


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. 


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

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"Saudi social media users ranked 7th in world," ed: Arab News, 2015.

"The Economist explains Why Saudis are ardent social media fans," ed: The Economist, 2015.

N. Lenze, "Social Media in the Arab World: Communication and Public Opinion in the Gulf States," European Journal of Communication, vol. 32, pp. 77-79, 2017.

J. A. Barnes and F. Harary, "Graph theory in network analysis," Social Networks, vol. 5, pp. 235-244, 1983.

S. Wasserman and K. Faust, Social network analysis: Methods and applications vol. 8: Cambridge university press, 1994.

P. Choudhary and U. Singh, "A Survey on Social Network Analysis for Counter-Terrorism," International Journal of Computer Applications, vol. 112, 2015.

Z. Zhao, S. Feng, Q. Wang, J. Z. Huang, G. J. Williams, and J. Fan, "Topic oriented community detection through social objects and link analysis in social networks," Knowledge-Based Systems, vol. 26, pp. 164-173, 2012.

S. Fortunato, "Community detection in graphs," Physics Reports, vol. 486, pp. 75-174, 2010.

B. Yang, J. Di, J. Liu, and D. Liu, "Hierarchical community detection with applications to real-world network analysis," Data & Knowledge Engineering, vol. 83, pp. 20-38, 2013.

D. Easley and J. Kleinberg, Networks,Crowds, and Markets: Reasoning about a Highly Connected World.: Cambridge University Press 2010.

D. Kempe, J. Kleinberg, and E. Tardos, "Maximizing the Spread of Influence through a Social Network," in KDD '03 Proceedings of the ninth ACM SIGKDD international conference on Knowledge discovery and data mining, New York, 2003, pp. 137-146.

S. J. Park, Y. S. Lim, and H. W. Park, "Comparing Twitter and YouTube networks in information diffusion: The case of the “Occupy Wall Street” movement," Technological Forecasting and Social Change, vol. 95, pp. 208-217, 2015.

M. C. Getchell and T. L. Sellnow, "A network analysis of official Twitter accounts during the West Virginia water crisis," Computers in Human Behavior, vol. 54, pp. 597-606, 2016.

O. Alheyasat, "Investigation and Analysis of Research Gate User’s Activities using Neural Networks," The International Arab Journal of Information Technology, vol. 2, 2016.

W. Maharani, Adiwijaya, and A. A. Gozali, "Degree centrality and eigenvector centrality in twitter," in Telecommunication Systems Services and Applications (TSSA), 2014 8th International Conference on, 2014, pp. 1-5.

U. Brandes, S. P. Borgatti, and L. C. Freeman, "Maintaining the duality of closeness and betweenness centrality," Social Networks, vol. 44, pp. 153-159, 2016.

A. G. Nikolaev, R. Razib, and A. Kucheriya, "On efficient use of entropy centrality for social network analysis and community detection," Social Networks, vol. 40, pp. 154-162, 2015.

H.-W. Shen, Community Structure of Complex Networks: Springer Berlin Heidelberg, 2013.

L. Tang and H. Liu, Community Detection and Mining in Social Media: Morgan & Claypool Publishers, 2010.

P. Zhang, C. Moore, and M. E. J. Newman, "Community detection in networks with unequal groups," Physical review E, vol. 93, p. 012303, 2016.

D. Kempe, Structure and Dynamics of Information in Networks. Los Angeles: University of South California, 2011.

S. Y. Bhat and M. Abulaish, "Overlapping Social Network Communities and Viral Marketing," in In proceeding of: International Symposium on Computational and Business Intelligence, New Delhi, 2013.

L. C. Freeman, "Centrality in social networks conceptual clarification," Social Networks, vol. 1, pp. 215-239, 1978.

L. Alvarez, K. Borsi, and L. Rodrigues, "The role of social network analysis on participation and placemaking," Sustainable Cities and Society, vol. 28, pp. 118-126, 2017.

J. Sun and J. Tang, "A Survey of Models and Algorithms for Social Influence Analysis," in Social Network Data Analytics, C. C. Aggarwal, Ed., ed Boston, MA: Springer US, 2011, pp. 177-214.

L. Tang and H. Liu, "Community detection and mining in social media," Synthesis Lectures on Data Mining and Knowledge Discovery, vol. 2, pp. 1-137, 2010.

T. Alahakoon, R. Tripathi, N. Kourtellis, R. Simha, and A. Iamnitchi, "K-path centrality: a new centrality measure in social networks," presented at the Proceedings of the 4th Workshop on Social Network Systems, Salzburg, Austria, 2011.

S. Papadopoulos, Y. Kompatsiaris, A. Vakali, and P. Spyridonos, "Community detection in social media," Data Mining and Knowledge Discovery, vol. 24, pp. 515-554, 2012.

F. Radicchi, C. Castellano, F. Cecconi, V. Loreto, and D. Parisi, "Defining and identifying communities in networks," Proceedings of the National Academy of Sciences of the United States of America, vol. 101, pp. 2658-2663, 2004.

M. E. Newman, "A measure of betweenness centrality based on random walks," Social Networks, vol. 27, pp. 39-54, 2005.

L. Katz, "A new status index derived from sociometric analysis," Psychometrika, vol. 18, pp. 39-43, 1953.

M. O. Jackson, Social and economic networks vol. 3: Princeton university press Princeton, 2008.

P. Bonacich, "Power and centrality: A family of measures," American journal of sociology, pp. 1170-1182, 1987.

M. Girvan and M. E. Newman, "Community structure in social and biological networks," Proceedings of the national academy of sciences, vol. 99, pp. 7821-7826, 2002.

M. E. Newman and M. Girvan, "Finding and evaluating community structure in networks," Physical review E, vol. 69, p. 026113, 2004.

A. Clauset, M. E. Newman, and C. Moore, "Finding community structure in very large networks," Physical review E, vol. 70, p. 066111, 2004.

J. Shi and J. Malik, "Normalized cuts and image segmentation," Pattern Analysis and Machine Intelligence, IEEE Transactions on, vol. 22, pp. 888-905, 2000.

U. Von Luxburg, "A tutorial on spectral clustering," Statistics and computing, vol. 17, pp. 395-416, 2007.

F. Meng, F. Zhang, M. Zhu, Y. Xing, Z. Wang, and J. Shi, "Incremental Density-Based Link Clustering Algorithm for Community Detection in Dynamic Networks," Mathematical Problems in Engineering, vol. 2016, p. 11, 2016.

D. Hansen, B. Shneiderman, and M. A. Smith, Analyzing social media networks with NodeXL: Insights from a connected world: Morgan Kaufmann, 2010.

M. A. Smith, B. Shneiderman, N. Milic-Frayling, E. M. Rodrigues, V. Barash, C. Dunne, T. Capone, A. Perer, and E. Gleave, "Analyzing (social media) networks with NodeXL," presented at the Proceedings of the fourth international conference on Communities and technologies, University Park, PA, USA, 2009.

E. A. Leicht and M. E. Newman, "Community structure in directed networks," Physical review letters, vol. 100, p. 118703, 2008.

S. Matei, "Analyzing Social Media Networks with NodeXL: Insights from a Connected World by Derek Hansen, Ben Shneiderman, and Marc A. Smith," International Journal of Human–Computer Interaction, vol. 27, pp. 405-408, 2011/02/23 2011.

R. Recuero, R. Araujo, and G. Zago, "How does social capital affect retweets?," in ICWSM, 2011.


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