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

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.