TÜRKİYE VE BİR GRUP ÜLKE İÇİN ÇATIŞMA VERİLERİNİN KUVVET YASASINA UYGUNLUĞU

Öz

Bugün birçok toplumsal sorun, bir bireye ya da gruba yönelik sürekli bir şiddeti içermektedir. Bu sorunlar; aile içi şiddet, kadına yönelik cinsel şiddet, sivil saldırılar, şiddetli çatışmalar, şiddetli protestolar, terör eylemleri ve ulusal güvenliğe yönelik siber saldırılar ile ticarete yönelik siber saldırılardır. Özellikle hükümetler ve politik yapıcılar bu şiddet olaylarının ölçülmesi sayesinde stratejiler geliştirerek birçok toplumsal olayın en düşük zarar ile sonuçlanmasını sağlamaktadır. Bugün, bu şiddet olaylarının şiddetini ölçmek için bir kuvvet yasası kullanılmaktadır. Genel olarak, kuvvet yasası bir olayın frekansının olayın artan boyutundan daha hızlı azaldığını tanımlar. Teknik olarak, bir "kuvvet yasası", birinin diğerinin gücü olarak değişen iki büyüklük arasındaki matematiksel ilişkiyi ifade etmektedir. Bu çalışmada, kuvvet yasalarını ve diğer uzun kuyruk dağılımları basitleştiren R’nin “poweRlaw” paketi kullanılmıştır. Çalışmada, 2014-2017 yılları arasında GDELT’ten elde edilen çatışma verileri kullanılarak; Irak, Suriye, Türkiye, Filistin, Ukrayna, Afganistan, İsrail ve Rusya’daki çatışmaların kuvvet yasası dağılımına uygun olup olmadığı test edilmiştir. Yapılan analizler sonucunda Türkiye ve Afganistan’daki çatışmaların kuvvet yasası dağılımına uygun olmadığı; Irak, Suriye, Filistin, Ukrayna, İsrail ve Rusya’daki çatışmaların kuvvet yasası dağılımına uygun olduğu bulunmuştur. Buradan

kuvvet yasası dağılımının ölçeğe göre değişmediği, yani farklı yerlerden elde

edilen verilerin aynı dağılım özelliklerine sahip olduğu sonucuna varılmıştır.

Anahtar Kelimeler

• Kuvvet Yasası Dağılımı,R,BigQuery,GDELT,Çatışma

SUITABILITY OF CONFLICT DATA FOR POWER LAW FOR TURKEY AND A GROUP OF COUNTRIES

Öz

Today, many social problems involve constant violence towards an

individual or a group. These problems are; domestic violence, sexual violence

against women, civil attacks, violent conflicts, violent protests, acts of

terrorism, and national security. In particular, governments and policy

makers have developed strategies through the measurement of these violent

events, resulting in the most harmful consequences of many social events.

Today, the power law distribution is used to measure the severity of these

violent incidents. In general, the power law defines that the frequency of an

event is decreasing faster than the increasing size of the event. Technically, a

"power law" refers to the mathematical relationship between two quantities

that change as the power of one's other. In this study, the "poweRlaw"

package of R, which simplifies power laws and other long tail distributions, is

used. Using the conflict data obtained from GDELT between 2014 and 2017,

Iraq, Syria, Turkey, Palestine, Ukraine, Afghanistan, Israel, and Russia are

tested whether their conflict data is suitable for power law. The results of the

analysis of the conflicts in Turkey and Afghanistan are not suitable for power

law distribution; the conflicts in Iraq, Syria, Palestine, Ukraine, Israel and

Russia are found to be suitable for distribution of power law. It is concluded

that the distribution of power law does not depend on the scale, that is, the

data obtained from various places has the same distributional characteristics.

Anahtar Kelimeler

• Power Law Distribution,R,BigQuery,GDELT,Conflict

Kaynakça

1. Abramowitz, Milton; Stegun, Irene A. (1972). Handbook of Mathematical Function with Formulas, Graphs, and Mathematical Tables. Volume 55 of Applied Mathematics Series, 10th edition, National Bureau of Standards.
2. Androtis, Nikos (2014). “The Power-Law Distribution (and You)”, https://www.efrontlearning.com/blog/2014/11/the-power-lawdistribution. html, (Erişim Tarihi 20.01.2018).
3. Arslan, İlker (2015). R ile İstatistiksel Programlama. İstanbul: Pusula Yayıncılık.
4. Bak, Per; Tang, Chao (1989). “Earthquakes as a Self-Organized Critical Phenomena”. Journal Geophysical Research, 94(B11), 15,635-15,637.
5. Biggs, Micheal (2005). “ Strikes a s F orest F ires: Chicago and Paris i n the Late 19th Century”. American Journal of Sociology, 110, 1714.
6. Cederman, Lars-Erik (2003). “Modeling the Size of Wars: From Billiard Balls to Sandpiles”, American Political Science Review, 97, 135.
7. Cioffi-Revilla, Claudio (1991). “On the Likely Magnitude, Extent, and Duration of the Iraq-UN War”. Journal of Conflict Resolution, 35, 387–411.
8. Clauset, Aaron; Young, Maxwell; Gleditsch Skrede, Kristian (2007). “On the Frequency of Severe Terrorist Events”. Journal of Conflict Resolution, 51, Number 1, 58-87.

9. Congleton, Roger D. (2002). “Terrorism, Interest-Group Politics, and Public Policy: Curtailing Criminal Modes of Political Speech”. The Independent Review, 7(1), 47-67.
10. Enders, Walter; Sandler, Todd (2006). The Political Economy of Terrorism. Cambridge: Cambridge University Press.
11. Federal Bureau of Investigation (1999). “Terrorism in the United States”. www.fbi.gov/publications/terror/terroris.htm.
12. Gartner, Scott S. (2004). “Making the International Local: The Terrorist Attack on the USS Cole, Local Casualties, and Media Coverage”. Political Communication, 21, 139–159.
13. Investopedia, http://www.investopedia.com/terms/1/80-20-rule.asp, (Erişim Tarihi: 20.06.2017).
14. Johnson, Neil F.; Spagat, Mike; Restrepo, Jorge A.; Becerra, Oscar; Bohorquez, Juan C.; Suarez, Nicolas; Restrepo, Maria; Elvira, M.; Zamara, Roberto (2006). “Universal Patterns Underlying Ongoing Wars and Terrorism”. Physics and Society, Cornell University Library.
15. Keating, Joshua (2013). “Mapping Protests and Violence Events in Egypt”, http://www.slate.com/blogs/the_world_/2013/08/20/an_interactive_map_that_documents_egypt_s_protests_and_violence.html, (Erişim Tarihi: 10.12.2017).
16. Lacina, Bethany (2006). “Explaining the Severity of Civil Wars”. Journal of Conflict Resolution, 50(2), 276-289.
17. Leetru, Kalve; Hoffa, Felipe (2015). “Analayzing the World’s News: Exploring the GDELT Project through Google BigQuery”, https://www.oreilly.com/ideas/analyzing-theworlds_ news_exploring_the_gdelt_project_through_googlebi, (Erişim Tarihi: 10.02.2018).
18. Li, Lun; Alderson, David; Doyle, John C.; Willinger, Walter (2005). “Towards a Theory of Scale-Free Graphs: Definition, Properties, and Implications”. Internet Mathematics, 2(4), 431-523.
19. Malamud, Bruce D.; Morein, Gleb; Turcotte, Donald L. (1998), “Forest Fires: An Example of Selforganized Critical Behavior”. Science, 281, 1840.
20. Muniruzzaman, A . N . M . ( 1957). “ On Measures of Location and Dispersion and Test of Hypothesis on a Pareto Distribution”. Calcutta Statistical Association Bulletin, 7(27), 115–126.
21. Navarro, Peter; Spencer, Aaron (2001). “Assesing the Costs of Terrorism”. Milken Institute Review, Fourth Quarter 2001, 16–31.
22. Newman, M. E. J. (2005). “Power Laws, Pareto Distributions and Zipf’s Law”. Contemporary Physics, 46(5), 323-351.
23. Overgaard, Per (1994). “The Scale of Terrorist Attacks as a Signal of Resources”. Journal of Conflict Resolution, 38, 452–478.
24. Richardson, Lewis F. (1948). “Variation of the Frequency of Fatal Quarrels with Magnitude”. Journal of the American Statistical Association, 43, 523.
25. Shubik, Martin (1997). “Terrorism, Technology, and the Socioeconomics of Death”. Comparative Strategy, 16, 399-414.
26. Simon, H erbert A . ( 1955). “ On a C lass of Skew Distribution Functions”. Biometrika, 42(3-4), 425-440.
27. The GDELT Project, http://gdeltproject.org/about.html#intro, (Erişim Tarihi: 10.08.2017).
28. Wilkinson, Paul (1997). “The Media and Terrorism: A Reassessment”. Terrorism and Political Violence, 9, 51–64.
29. Zipf, George K. (1949). Human Behavior and the Principle of Least Effort. Cambridge: Addison-Wesley Press.