Determination of Influential Countries by Cultural and Geographical Parameters

Yıl 2020, , 179 - 188, 24.02.2020

İhsan Tuğal , Ali Karcı

https://doi.org/10.18506/anemon.563211

Cited By: 1

Öz

The
cultural and geographical situation of countries cover the most important
factors determining the relations between countries. In this study, a new
method was proposed to identify the influential countries. Similarities were
calculated by religion, language, zone, and landmass information of countries.
This data was transformed into a graph structure.  Central countries were determined by Shannon
and Karcı entropy over country similarities. The number of similarities and
similarity ratios of each country with other countries were used when identifying
the influential countries. The difference of Karcı entropy from Shannon, that
the effect of these two values ​​can be adjusted by the alpha. With the
parameters used, the determination of countries' leadership will reveal new
analysis and perspectives in international relations.

Anahtar Kelimeler

country associations, social computing, graph entropy, influential countries, social network

Kültürel ve Coğrafi Parametrelere Göre Lider Ülkelerin Tespiti

Öz

Ülkelerin
kültürel ve coğrafi durumu, ülkeler arasındaki ilişkileri belirleyen en önemli
faktörlerdir. Bu çalışmada çizge entropi kullanılarak, sosyal ağ analizi
yöntemleri ile lider ülkeler tespit edildi. Ülke benzerlikleri kültürel ve
coğrafi parametreler olan din, dil, bölge, kıta bilgileri ile ölçüldü. Benzerlikler
kullanılarak ülkelerin ilişki yapısı çizge yapısında çıkarıldı. Sosyal ağ
yapısında merkezi ülkelerin tespiti için geleneksel merkezilik ölçümleri yerine
Shannon ve Karcı entropi kullanıldı ve elde edilen sonuçlara göre bu iki
entropi türü kıyaslandı. Karcı entropi de Shannon’dan farklı olarak bu iki
değerin ölçümdeki etkisinin alfa ile ayarlanabildiği gösterildi. Bu çalışmada
kullanılan parametrelerle elde edilen sonuçlar ve önerilen yöntemler ile
ülkelerin liderliğinin ve etkinliğinin belirlenmesi uluslararası ilişkilerde
yeni analizler ve bakış açıları ortaya çıkaracaktır.

Anahtar Kelimeler

sosyal hesaplama, çizge entropi, lider ülkeler, ülke birliktelikleri, Sosyal Ağ

Kaynakça

• Borgatti, S. P., M. G. Everett, and L. C. Freeman. 2002. “UCINET 6 For Windows: Software for Social Network Analysis, Analytic Technologies, Harvard, MA.” Analytic Technologies.
• Borgatti, Stephen P. 2005. “Centrality and Network Flow.” Social Networks 27(1):55–71.
• Chen, Duanbing, Linyuan Lü, Ming Sheng Shang, Yi Cheng Zhang, and Tao Zhou. 2012. “Identifying Influential Nodes in Complex Networks.” Physica A: Statistical Mechanics and Its Applications 391(4):1777–87.
• Durland, Maryann M. and Kimberly A. Fredericks. 2005. “An Introduction to Social Network Analysis.” New Directions for Evaluation (107):5–13.
• Ernesto, Trucco. 1956. “A Note on the Information Content of Graphs.” The Bulletin of Mathematical Biophysics 18(2):129–135.
• Fei, Liguo and Yong Deng. 2017. “A New Method to Identify Influential Nodes Based on Relative Entropy.” Chaos, Solitons and Fractals 104:257–67.
• Freeman, Linton C. 1978. “Centrality in Social Networks Conceptual Clarification.” Social Networks 1(3):215–39.
• Gürsakal, Necmi. 2009. Sosyal Ağ Analizi. Dora Yayınları.
• Huntington, Samuel P. 2001. Medeniyetler Çatışması. Vadi Yayınları.
• Karagöz, D. and Yüncü H. R. 2013. “Examining Research Topics of Doctoral Theses Written in the Field of Tourism by Social Network Analysis.” Adıyaman University Journal of Social Sciences 15.
• Karcı, Ali. 2018. “Notes on the Published Article ‘Fractional Order Entropy: New Perspectives.’” Optik - International Journal for Light and Electron Optics 171:107–8.
• Lichman, M. n.d. “UCI Machine Learning Repository [Http://Archive.Ics.Uci.Edu/Ml].” Irvine, CA: University of California, School of Information and Computer Science. Retrieved January 4, 2018 (http://archive.ics.uci.edu/ml).
• Linyuan, L. L. and Tao Zhou. 2011. “Link Prediction in Complex Networks: A Survey.” Physica A: Statistical Mechanics and Its Applications.
• M. Bastian, S. Heymann, M. Jacomy et al. 2009. “Gephi: An Open Source Software for Exploring and Manipulating Networks‎.” in Proceedings of International AAAI Conference on Web and Social Media‎.
• Mowshowitz, Abbe. 1968. “Entropy and the Complexity of Graphs: I. An Index of the Relative Complexity of a Graph.” The Bulletin of Mathematical Biophysics 30(1):175–204.
• Nie, Tingyuan, Zheng Guo, Kun Zhao, and Zhe Ming Lu. 2016. “Using Mapping Entropy to Identify Node Centrality in Complex Networks.” Physica A: Statistical Mechanics and Its Applications 453:290–97.
• Padgett, John F. 2010. “Open Elite? Social Mobility, Marriage, and Family in Florence, 1282–1494*.” Renaissance Quarterly 63(02):357–411.
• Peng, Sancheng, Aimin Yang, Lihong Cao, Shui Yu, and Dongqing Xie. 2017. “Social Influence Modeling Using Information Theory in Mobile Social Networks.” Information Sciences 379:146–59.
• Rashevsky, N. 1955. “Life, Information Theory, and Topology.” The Bulletin of Mathematical Biophysics 17(3):229–35.
• Raymond, Chang. 2005. Physical Chemistry for the Biosciences.
• Scott, J. P. 2000. Social Network Analysis: A Handbook.
• Shannon, C. E. 1951. “Prediction and Entropy of Printed English.” Bell System Technical Journal 30(1):50–64.
• Shetty, Jitesh and Jafar Adibi. 2006. “Discovering Important Nodes through Graph Entropy the Case of Enron Email Database.” Pp. 74–81 in.
• Tuğal, İ. and A. Karcı. 2019. “Comparisons of Karcı and Shannon Entropies and Their Effects on Centrality of Social Networks.” Physica A: Statistical Mechanics and Its Applications 523.
• Tuğal, İhsan and Ali Karcı. 2016. “Computing Association between Countries.” Pp. 87–92 in International Artificial Intelligence and Data Processing Symposium (IDAP 2016).
• Tuğal, İhsan, Mehmet Kaya, and Taner Tuncer. 2013. “Link Prediction in Disease and Drug Networks.” Pp. 46–50 in 6-th International Conference of Advanced Computer Systems and Networks: Design and Application (ACSN 2013).
• Wasserman, Stanley and Joseph Galaskiewicz. 2012. Advances in Social Network Analysis: Research in the Social and Behavioral Sciences.
• Wolfe, Alvin W. 1997. “Social Network Analysis: Methods and Applications.” American Ethnologist 24(1):219–20.
• Zhang, Qi, Meizhu Li, and Yong Deng. 2018. “Measure the Structure Similarity of Nodes in Complex Networks Based on Relative Entropy.” Physica A: Statistical Mechanics and Its Applications.