The tools used to examine modern motion pictures are changing. Rather than relying on the traditional audiovisual approach, the contemporary method is known as social network analysis. “With the idea of social network analysis, we propose a novel way to analyze movie videos from the perspective of social re-lationships rather than audiovisual features”(Weng, Chu, & Wu, 256). This indicates that the technique of audiovisual analysis is gradually being replaced by a more sophisticated observance system. Through social network analysis, the hidden significances behind movie films are revealed, ones that may not be easily detected.

The film-analysis strategy is increasingly a calculated perspective. A study conducted in 1998 aids with the mathematical processes behind RoleNet: “We hope that our work will stimulate further studies of small-world networks. Their distinctive combination of high clustering with short characteristic path length cannot be captured by traditional approximations such as those based on regular lattices or random graphs” (Watts & Strogatz, 442). As the traditional audiovisual methods are overwritten tools such as lattices and charts must be replaced with new elements, such as big data. As a result, one is able to utilize the updated strategey of social network analysis.

Though the new technique has been developed, there is undoubtedly room for improvement. “They fail to extract story information that varies over time. Therefore, future work will improve the method by updating the community tracking rules and functions over time. We will browse and abstract video with community and sequence information. Scenes with community members can be connected to cluster communities. Scenes can be hierarchically browsed via this method” (Park, 59). By incorporating the community tracking systems and overall functions of social network analysis, the technique will be upgraded further. This is significant in terms of being able to better break down digital media, as that of motion pictures. With enhanced strategies, better forms of analysis can be coordianted to bring about more hidden, yet significant, findings previously undetected by observers.

References (in order of appearance):

Weng, C. Y., W. T. Chu, and J. L. Wu. 2009. “RoleNet: Movie Analysis from the Perspective of Social Networks.” IEEE Transactions on Multimedia 11 (2): 256–71. doi:10.1109/TMM.2008.2009684.

Watts, D. J, and S. H Strogatz. 1998. “Collective Dynamics of ‘small-World’ Networks.” Nature 393 (6684): 440–42. doi:10.1038/30918.

Park, Seung-Bo, Kyeong-Jin Oh, and Geun-Sik Jo. 2012. “Social Network Analysis in a Movie Using Character-Net.” Multimedia Tools and Applications 59 (2): 601–27. doi:10.1007/s11042-011-0725-1.