A Semi-Automated Method of Network Text Analysis Applied to 150 Original Screenplays

Proceedings of the Joint Workshop on Social Dynamics and Personal Attributes in Social Media, p. 68, June 2014

9 Pages Posted: 28 Jun 2014

Date Written: June 26, 2014

Abstract

In this paper I apply a novel method of network text analysis to a sample of 150 original screenplays. That sample is divided evenly between unproduced, original screenplays (n =75) and those that were nominated for Best Original Screenplay by either the Academy of Motion Picture Arts & Sciences or by major film critics associations (n = 75). As predicted, I find that the text networks derived from unproduced screenplays are significantly less complex, i.e. they contain fewer concepts (nodes) and statements (links). Unexpectedly, I find that those same networks are more cohesive, i.e. they exhibit higher density and coreness.

Keywords: network analysis, content analysis, network text analysis, screenplay, film, film industry, Academy Awards, movies, motion pictures

Suggested Citation

Hunter, Starling David, A Semi-Automated Method of Network Text Analysis Applied to 150 Original Screenplays (June 26, 2014). Proceedings of the Joint Workshop on Social Dynamics and Personal Attributes in Social Media, p. 68, June 2014, Available at SSRN: https://ssrn.com/abstract=2459674

Starling David Hunter (Contact Author)

Carnegie Mellon University ( email )

5032 Forbes Ave.
Qatar Office SMC 1070
Pittsburgh, PA 15289
United States

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