DÜNYADAKİ ÇATIŞMALARIN SOSYAL AĞ ANALİZİ YÖNTEMİYLE İNCELENMESİ

Abstract

Social network members are a group of actors who are linked to one or more clusters of relationships (Knoke & Yang, 2008). The actors or technically nodes of social networks may be living beings, such as people or groups of people, or sometimes inanimate beings (Kolaczyk, 2009). Examples of living beings are patients or doctors in a hospital. However, social units such as hospitals or objects such as written texts can be given as examples of inanimate objects (O'Malley & Marsden, 2008). In the complex structure of social relations, people are interconnected in many networks to represent a network of relationships. It is possible to analyze these complex relationships with the “Social Network Analysis" method. Social network analysis allows seeing structures that are not visible to the naked eye (Kadushin, 2005). This allows the hidden structures to be seen more clearly. The main purpose of social network analysis is to determine and interpret the distances of social ties between actors. In social network analysis, it is aimed to understand the network structure by description, visualization and modeling. The main purpose of this study is to give a new perspective to the conflict situations in the world by using social network analysis method. The data used in the study was taken from the GDELT dataset. GDELT is the largest, most comprehensive and highest resolution open database ever created in human history. In the study, firstly, the number of news about the conflict news in world media between 1979 and 2018 was analyzed using SQL. As a result of the analysis, the most frequent countries mentioned together in the news were found. In order to analyze the dataset, we first transform it into the form of a neighborhood matrix, then analyze the data using the “igraph" package of the R software. This package calculates a wide range of measures of centrality for each node in the network. Thus, the quantitative ordering of “importance" and “effect" of each node in the network has been analyzed rapidly. The results of the study are very important in terms of the theory of power. Firstly, it was found that the USA is the biggest actor in the conflicts in the world and is followed by Russia. In this context, it is possible to say that the greatest actors in the formation of conflicts in the world today are the USA and Russia, respectively. Today, these two great actors have the greatest powers of the world and control almost every country in the world. It can be said that almost all the conflicts in the world today are related to these two countries. Again, it can be said that these two actors have great effect in the change of country regimes and borders in the world today. When the results of the study are evaluated from the point of view of the theory of power, it is unlikely that these two states will enter into war (or militarized conflict) because the USA and Russia have a relatively equal power balance. But since the USA and Russia are stronger than other states, they are highly likely to enter battle (or militarization) to strengthen their position in the world. Because the balance of power theory says that in the case of equality of power, victory becomes problematic and deterring aggression as it increases uncertainty. On the other hand, when evaluated in terms of power imbalance, the USA and Russia are more aggressive towards other states because they have a higher chance of being successful against other states. In this case, the weaker countries will not dear to conflict with these two countries, and this will give them greater convenience in reaching the goals of the stronger parties. It also shows that the USA and Russia have the highest centrality in the network and they have the greatest activity and greatest efficiency in the conflicts. Secondly, it is found that few countries have many connections and many countries have few connections. These results show that the social network structure is independent of the scale. Finally, it is seen that the total network consists of 9 groups and the largest roup has 31 node points and 31 unique borders. The other groups are composed of two groups. Thus, the formation of the cluster with 31 nodes worldwide conflict can be concluded to have the greatest impact. It was also observed that the USA is the biggest actor in the cluster with 31 nodes. (English) [ABSTRACT FROM AUTHOR] Son yıllarda bilişim ve bulut teknolojilerinde yaşanan gelişmeler sosyal ağ analizinin bilimsel çalışmalarda daha fazla kullanılmasını sağlamıştır. Sosyal ağ analizi ile ilgili yapılan çalışmalarda gerçek ağların geleneksel ağ teorisinin varsayımlarından oldukça farklı davrandıkları sonucuna varılmıştır. Geleneksel olarak, gerçek ağların, ortalama olarak yaklaşık aynı sayıda bağlantıya sahip düğümlerin çoğunluğuna sahip olması gerekmektedir. Fakat modern ağ çalışmaları, gerçek ağ düğümlerinin çoğunun çok az sayıda olduğunu ve tersine, çok fazla sayıda bağlantı içeren bazı düğümler olabileceğini göstermektedir. Bu tür kuvvet yasası (ölçeğe bağlı olmayan), biyolojik ağlardan sosyal ağlara kadar birçok gerçek ağda bulunabilmektedir. Bu çalışmanın amacı, dünyadaki çatışmaların sosyal ağ analizi yöntemi ile incelenmesidir. Çalışmada 1979-2018 yılları arasında GDELT veri setinden elde edilen çatışma verileri R yazılımının “igraph" paketi kullanılarak analiz edilmiştir. Yapılan analizler sonucunda dünyadaki çatışmalarda en büyük iki aktörün sırasıyla ABD ve Rusya'nın olduğu sonucuna varılmıştır. Elde edilen bu sonuçlardan dünyada yaşanan çatışmaların neredeyse tümünün bu iki ülke ile ilişkili olduğu söylenebilir. Yine bugün dünyada ülke rejimlerinin ve sınırlarının değişmesinde bu iki aktörün büyük etkisi vardır. Ayrıca analizler sonucunda elde edilen ağın yapısında az sayıda ülkenin çok sayıda bağlantıya, çok sayıda ülkenin de az sayıda bağlantıya sahip olduğu bulunmuştur. Elde edilen bu sonuçlar, ağın yapısının ölçekten bağımsız olduğunu göstermektedir. (Turkish) [ABSTRACT FROM AUTHOR] Copyright of Journal of Marmara University Social Sciences Institute / Öneri is the property of Marmara University, Institute of Social Sciences and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)