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Today, complex network analysis is widely used in
examining interrelated systems. Complex network analysis is
used in various fields such as brain research, health,
cybersecurity, education, e-commerce, urban and transportation
planning, and social networks. The subfield of complex network
analysis that examines social relationships is called social
network analysis. Social network analysis examines network
parameters using nodes and connections between nodes. Actormovie collaboration networks, a type of social network analysis,
are a type of network that examines collaboration between actors
playing in the same movie.
This study used data compiled from the website Box Office,
which records movie data. Within the scope of the study, a
complex actor-movie collaboration network consisting of Turkish
movies made between 2012 and 2022 was created. The number of
movies examined was 1803. The created dataset has 5182 nodes
(actors) and 55216 links (collaborations). Using the obtained
dataset, general analyses were conducted, such as the most
collaborating actors, the distribution of movie numbers and
genres by year, and the most successful actors in the industry
according to movie revenues. The actor- movie collaboration
network was examined using complex network analysis
parameters. Regarding network parameters, metrics belonging to
the network structure were calculated, such as node degree
distribution, average shortest path in the network, degree
centrality, average clustering coefficient, and network density.
The network metrics calculated the average shortest path as 3.3,
network diameter as 8, average degree as 21.3, average clustering
coefficient as 0.774, and network density as 0.004. In addition, the
actor movie network was visualized using Gephi software to
perform clustering and community analyses. The node degree
distribution graph of the actors was plotted on the log-log axis.
According to the metric analysis results, it was observed that the
actor- movie collaboration network consisting of Turkish movie
was characterized by real network parameters such as high
clustering, hub node, and average distance.
International Conference on Advanced Technologies, Computer Engineering and Science
ICATCES
Elanur GÜL
Sait DEMİR