Journals / Erciyes İletişim Dergisi / 2020 / Cilt: 7 - Sayı: 2

The Degrees of Separation in Turkish Cinema: The Sühely Eğriboz Number

Türk Sinemasında Ayrılma Dereceleri: Sühely Eğriboz Sayısı

Pages
1199–1212
Publication Date
2022-10-11
DOI
—
🏛️Bibliographic metadata and full text access for this article are provided via DergiPark.
DergiPark Record ↗
✨

AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

Our results show that actor Sühely Eğriboz is the center node of Turkish Cinema graph with the lowest closeness centrality and average actor number value.

📌 3 Key Takeaways

🎯
Objective & Hypothesis:We live in a small-world where a person can reach another person via -on average- six steps by knowing a friend of a friend and with digitalization.
📊
Key Findings & Data:One of the important questions in small-world research is about which node being in the center of the small- world.
💡
Conclusion & Impact:Our results show that actor Sühely Eğriboz is the center node of Turkish Cinema graph with the lowest closeness centrality and average actor number value.
🔬Design:Research Article
📍Scope:Comprehensive Sample
⚙️Variables:Sinema · Derece · Ayrım

Abstract

We live in a small-world where a person can reach another person via -on average- six steps by knowing a friend of a friend and with digitalization. One of the important questions in small-world research is about which node being in the center of the small- world. In here, with the central node definition, we refer to the node that can connect to all other nodes in the small-world by the shortest paths. In this study, we analyze the connection among actors/actresses of the Turkish Cinema and aim to define the center node in it. We use a graph analysis method that creates an Actor-Movie bipartite graph and projects it into a one-mode Actor-Actor graph to find the center node in the Turkish Cinema. Our results show that actor Sühely Eğriboz is the center node of Turkish Cinema graph with the lowest closeness centrality and average actor number value. Although there are paths that are longer than six steps, Sühely Eğriboz can reach any given actor/ actress with an average 3.142 steps.

Özet

Bir bireyin bir başka bireye, dijitalleşme ve kişisel bağlantılar aracılığıyla (arkadaşımın arkadaşı) ortalama altı adımda ulaşabileceği küçük bir dünyada yaşıyoruz. Küçük dünya olgusunun ele alındığı araştırmalarda önemli bir soru da hangi düğümün (birey, nesne vb.), mevcut yapının merkezinde yer aldığıdır. Burada, merkez düğüm tanımıyla küçük dünya yapısı içinde yer alan tüm diğer düğümlere en kısa bağlantı yoluna sahip olan düğümü ifade ediyoruz. Bu çalışmada; Türk Sinemasında yer alan aktörler/aktrisler arasında var olan bağlantıların analiz edilmesiyle birlikte, merkez düğümün tanımlanması amaçlanmıştır. Türk Sinemasındaki merkez düğümü bulmak için; Aktör-Film iki taraflı çizgesini oluşturan ve bunu tek taraflı Aktör-Aktör çizgesine indirgeyen çizge analiz yöntemi kullanılmıştır. Çalışma sonuçları, Süheyl Eğriboz’un en düşük yakınlık merkeziliği ve ortalama aktör sayısı değerleri ile merkezi düğüm olduğunu ortaya koymuştur. Altı adımdan daha uzun yolların var olmasına rağmen, Sühely Eğriboz çizge içinde verilen herhangi bir aktöre/aktriste ortalama 3.142 adımda ulaşabilmektedir.

🔖

Cite This Article

ABANOZ, E. (2022). The Degrees of Separation in Turkish Cinema: The Sühely Eğriboz Number. Erciyes İletişim Dergisi, Cilt: 7 - Sayı: 2, 1199–1212. https://ajindex.com/articles/501838

📄 Full Text PDF Viewer

📄

PDF görüntüleyici hazırlanıyor...

References (11)

  1. Abraham, A., Hassanien, A. E., & Snášel, V. (Eds.). (2010). Computational Social Network Analysis: Trends, Tools and Research Advances. Dordrecht, Netherlands: Springer. Aylward, B. S., Odar, C. C., Kessler, E. D., Canter, K. S., & Roberts, M. C. (2012). Six Degrees of Separation: An Exploratory Network Analysis of Mentoring Relationships in Pediatric Psychology. Journal of Pediatric Psychology, 37(9), 972–979. https://doi. org/10.1093/jpepsy/jss078 Barabási, A.-L. (2002). Linked: The New Science of Networks. Cambridge, MA: Perseus Publishing. Barabási, A.-L. (2016). Network Science (1st Edition). Cambridge, UK: Cambridge University Press.
  2. Barrat, A., Barthelemy, M., & Vespignani, A. (2008). Dynamical processes on complex networks. Cambridge: Cambridge University Press.
  3. Csardi, G., & Nepusz, T. (2006). The igraph software package for complex network research. InterJournal, Complex Systems, 1695. Easley, D., & Kleinberg, J. (2010).
  4. Networks, Crowds and Markets: Reasoning about a Highly Connected World (1st Edition). New York, NY: Cambridge University Press. gordonm888. (2015, September 19). 18 prolific actors who appeared in 120+ films [Online Database]. Retrieved February 5, 2019, from http://www.imdb.com/list/ ls053612898/ Harary, F. (1969).
  5. Graph Theory. Boston, MA: Addison-Wesley Publishing Company. Hautz, W. E., Krummrey, G., Exadaktylos, A., & Hautz, S. C. (2016). Six degrees of separation: the small world of medical education. Medical Education, 50(12), 1274–1279. https://doi.org/10.1111/medu.13102
  6. Jackson, M. O. (2010). Social and Economic Networks. Princeton, NJ: Princeton University Press.
  7. Karinthy, F. (1929). Chains. In E. Jankó (Ed.), A. Makkai (Trans.), Everything is Different. Budapest. Kleinberg, J., & Tardos, É. (2006). Algorithm Design. Boston: Pearson/Addison-Wesley. Milgram, S. (1967). The Small-World Problem. Psychology Today, 1(1), 61–67.
  8. Newman, M. (2010). Networks: An Introduction. New York, NY: Oxford University Press Inc. Newman, M., Barabási, A.-L., & Watts, D. J. (2006). The Structure and Dynamics of Networks (1st Edition). Princeton, NJ: Princeton University Press.
  9. Pattison, P. (1993). Algebraic Models for Social Networks. New York, NY: Cambridge University Press.
  10. Python Dev Team. (2018). Python: A programing language. Beaverton, OR: Python Software Foundation. Retrieved from https://www.python.org
  11. R Core Team. (2017). R: A language and environment for statistical computing. Vienna, Austria: R Foundation for Statistical Computing