Investigation of cinematic genre diversity based on social network analysis: the lost ring of the Iranian cinema industry

Abstract

PurposeMovies critics believe that the diversity of Iranian cinematic genres has decreased over time. The paper aims to answer the following questions: What is the impact of the continuous cooperation between the key nodes on the audience's taste, uniformity of the cinematic genres and the box office? Is there any relationship between the importance of actors in the actors' network and their popularity?Design/methodology/approachIn the artistic world, artists' relationships lead to a network that affects individuals' commercial or artistic success and defines the artwork's value. To study the issue that the diversity of Iranian cinematic genres has decreased over time, the authors utilized social network analysis (SNA), in which every actor is considered a node, and its collaboration with others in the same movies is depicted via edges. After preparing the desired dataset, networks were generated, and metrics were calculated. First, the authors compared the structure of the network with the box office. The results illustrated that the network density growth negatively affects box office. Second, network key nodes were identified, their relationships with other actors were inspected using the Apriori algorithm to examine the density cause and the cinematic genre of key nodes, and their followers were investigated. Finally, the relationship between the actors' Instagram follower count and their importance in the network structure was analyzed to answer whether the generated network is acceptable in society.FindingsThe social problem genre has stabilized due to continuous cooperation between the core nodes because network density negatively impacts the box office. As well as, the generated network in the cinema is acceptable by the audience because there is a positive correlation between the importance of actors in the network and their popularity.Originality/valueThe novelty of this paper is investigating the issue raised in the cinema industry and trying to inspect its aspects by utilizing the SNA to deepen the cinematic research and fill the gaps. This study demonstrates a positive correlation between the actors' Instagram follower count and their importance in the network structure, indicating that people follow those central in the actors' network. As well as investigating the network key nodes with a heuristic algorithm using coreness centrality and analyzing their relationships with others through the Apriori algorithm. The authors situated the analysis using a novel and original dataset from the Iranian actors who participated in the Fajr Film Festival from 1998 to 2020.

In the Arena of the Content War: A Social Network Analysis Approach for Content Differentiation in VOD Platforms

“…The second point is that people tend to show interest in genres where they can observe their daily life needs and concerns being portrayed. [17].…”

“…Although machine learning methods have been widely used to analyze VOD platform datasets [31,32], more attention should be given to other techniques, such as SNA. Utilizing SNA enables researchers to comprehensively understand the relationships between various phenomena, assess audience preferences, explore the interplay between genres and actors, analyze information dissemination patterns to enhance digital marketing, and model and examine distribution velocity systematically and holistically [17,33].…”

“…In other words, it serves as a bridge between different keywords, providing an opportunity for innovative utilization of hybrid keywords that blend genres. As well as, it has been proven that there is a positive correlation between the diversity of the genre or topic of a film and the level of public reception, as this breadth is responsible for satisfying different segments of the audience [17].…”

Collaboration and Competition: A Social Network Analysis of Thailand’s Music Industry

“…In addition, after the small-world experiment in 1994, the industry has seen a surge in studies exploring its network structure, such as Ahmed et al (2007), Spitz and Horvát (2014), Kagan et al (2020), andNoroozian et al (2022). Additionally, research has focused on the networks and relationships among the various roles within the industry.…”