Visualizing Patterns, Communities, and Opportunities for Joint Investments in the Film Industry: A Social Network Analysis Perspective

Maghsoudi, Mehrdad; Amini, Mohammad Ali; Aliakbar, Saeid; HabibiPour, Sajjad

Visualizing Patterns, Communities, and Opportunities for Joint Investments in the Film Industry: A Social Network Analysis Perspective

Document Type : Call for Special Issue on Development of Creative Industries

Authors

¹ Shahid Beheshti

² School of Management, Sharif University of Technology

³ Educational Department of Industrial Engineering, Technical and Engineering Faculty of Damghan University, Semnan Province

⁴ Faculty of Mechanical Engineering, Khwaja Nasiruddin Tusi University of Technology

Abstract

The global film industry has witnessed increased collaboration and international investment in recent years. However, a comprehensive analysis of joint investments in this domain is lacking. This study employs social network analysis (SNA) to examine collaboration opportunities and joint investments in the film industry. A network consisting of 150 countries based on shared creative themes in their film productions was constructed, comprising over 7,800 connections. Utilizing centrality measures, key countries such as the United States, China, and the United Kingdom were identified as influential hubs with strong potential to drive industry growth through partnerships.

Further analysis through community detection unveiled distinct thematic clusters united by collaborative creative efforts. For instance, the "Global Thrill Seekers" community creates action films, while the "Cultural-Social Cinema" group deals with global cultural and social issues. Each community presents unique perspectives for international collaboration and co-production. This analysis provides valuable insights into the structure and dynamics of the global film network, while highlighting potential avenues for future investments and collaboration. This research underscores the importance of utilizing SNA techniques to optimize decision-making regarding joint investments and predicting outcomes, serving as a model for data-driven participation analysis in creative industries.

Keywords