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A Network Text Analysis of David Ayer’s Fury
Abstract
Network Text Analysis (NTA) involves the creation of networks of words and/or concepts from linguistic data. Its key insight is that the position of words and concepts in a text network provides vital clues to the central and underlying themes of the text as a whole. Recent research has relied on inductive approaches to identify these themes. In this study we demonstrate a deductive approach that we apply to the screenplay of the 2014 World War II-era film Fury. Specifically, we first use genre expectations theory to establish prior expectations as to the key themes associated with war films. We then empirically test whether words and concepts associated with the most influentially-positioned nodes are consistent with themes common to the war-film genre. As predicted, we find that words and concepts associated with the least constrained nodes in the text network were significantly more likely to be associated with the war, action, and biography genres and significantly less likely to be associated with the mystery, science-fiction, fantasy, and film-noir genres.
Keywords: content analysis, text analysis, network text analysis, semantic network analysis, film studies, screenplay, screenwriting, war movies, World War II, tanks
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Altman, R. (1984). A semantic/syntactic approach to film genre. Cinema Journal, 6-18.
Barnhart, R. K. (Ed.). (1995). The Barnhart Concise Dictionary of Etymology. New York, NY: Harper-Collins.
Beam, E., Appelbaum, L. G., Jack, J., Moody, J., & Huettel, S. A. (2014). Mapping the semantic structure of cognitive neuroscience. Journal of Cognitive Neuroscience, 26(9), 1949-1965.
Bignell, J. (2002). Media semiotics: An Introduction. Manchester, UK: Manchester University Press.
Box Office Mojo (2015), Retrieved April 23, 2015, from http://www.boxofficemojo.com/movies/?id=savingprivateryan.htm
Burt, R. S. (2000). The network structure of social capital. Research in Organizational Behavior, 22, 345-423.
Diesner, J., & Carley, K. M. (2005). Revealing social structure from texts: meta-matrix text analysis as a novel method for network text analysis. Causal mapping for information systems and technology research: Approaches, advances, and illustrations, 81-108.
Diesner, J. (2012). Uncovering and managing the impact of methodological choices for the computational construction of socio-technical networks from texts. Carnegie-Mellon University, Pittsburgh PA. Institute of Software Research International.
Eberwein, R. (2009). The Hollywood War Film. Malden, MA: John Wiley & Sons.
Eliashberg, J., Hui, S. K., & Zhang, Z. J. (2007). From story line to box office: A new approach for green-lighting movie scripts. Management Science, 53(6), 881-893.
Field, S. (2005). Screenplay: The Foundations of Screenwriting (2nd ed.). New York: Delta.
Fischer-Starcke, B. (2009). Keywords and frequent phrases of Jane Austen's Pride and Prejudice: A corpus-stylistic analysis. International Journal of Corpus Linguistics, 14(4), 492-523.
Grbic, D., Hafferty, F. W., & Hafferty, P. K. (2013). Medical school mission statements as reflections of institutional identity and educational purpose: A network text analysis. Academic Medicine, 88(6), 852-860.
Hauge, M. (1991). Writing screenplays that sell. New York, NY: Harper-Collins.
Hoad, T. F. (Ed.). (1993). The Concise Oxford Dictionary of English Etymology. Oxford: Oxford University Press.
Hunter, S. (2014). A Novel Method of Network Text Analysis. Open Journal of Modern Linguistics, 4(2), 350-66.
Hunter, S., & Singh, S. (2015). A Network Text Analysis of Fight Club. Theory and Practice in Language Studies, 5(4), 737-749.
Hunter, S., & Smith, S. (2013). Thematic and Lexical Repetition in a Contemporary Screenplay. Open Journal of Modern Linguistics, 3(1), 9-19.
Hunter, S., & Smith, S. (2014). A Network Text Analysis of Conrad’s Heart of Darkness. English Linguistics Research, 3(2), p39.
Light, R. (2014). From Words to Networks and Back: Digital Text, Computational Social Science, and the Case of Presidential Inaugural Addresses. Social Currents, 1(2), 111-129.
Lim, S., Berry, F. S., & Lee, K. H. (2015). Stakeholders in the Same Bed with Different Dreams: Semantic Network Analysis of Issue Interpretation in Risk Policy Related to Mad Cow Disease. Journal of Public Administration Research and Theory, in press.
Martin, M. K., Pfeffer, J., & Carley, K. M. (2013). Network text analysis of conceptual overlap in interviews, newspaper articles and keywords. Social Network Analysis and Mining, 3(4), 1165-1177.
Morris, T. (2014). Networking vehement frames: neo-Nazi and violent jihadi demagoguery. Behavioral Sciences of Terrorism and Political Aggression, 6(3), 163-182.
Nerghes, A., Lee, J-S., Groenewegen, P. & Hellsten, I. (2015). Mapping Discursive Dynamics of the financial crisis: a structuralist perspective of concept roles in semantic networks. Computational Social Networks, 2(16), 1-29.
Rotten Tomatoes (2015). Retrieved August 4, 2015, from http://www.rottentomatoes.com /m/fury_2015
Shim, J., Park, C., & Wilding, M. (2015). Identifying policy frames through semantic network analysis: an examination of nuclear energy policy across six countries. Policy Sciences, 48(1), 51-83.
Shortell, T. (2011). The conflict over origins: A discourse analysis of the creationism controversy in American newspapers. Mass Communication and Society, 14(4), 431-453.
Snyder, B. (2005). Save the cat! The last book on screenwriting you’ll ever need. Studio City, CA: M. Wiese Productions.
Watkins, C. (Ed.). (2011). The American Heritage Dictionary of Indo-European Roots. Boston: Houghton Mifflin Harcourt.
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