Modeling Conflict: Representations of Social Groups in Present-Day Dutch Literature

Abstract

This essay responds to a lack of scholarly attention for conflict as a narrative mechanism since the formalist models of Vladimir Propp and Algirdas Julien Greimas. Building on recent developments within cultural analytics, the essay argues for a new understanding of narrative conflict by integrating classic narratological models with data-driven, statistical methods. It does so by (a) proposing two computational models of conflict based on theoretical insights from narratology, conflict studies, and network theory, (b) applying those models to a sample corpus of 170 present-day Dutch novels, and (c) briefly illustrating the narratological value of the results by interpreting the representation of social groups in two novels from the corpus -Bart Koubaa's De Brooklynclub (2012) and Leon de Winter's VSV (2012)in light of the statistical patterns found for the corpus as a whole. The analyses of dyadic (two characters) and triadic (three characters) conflict leads to two central conclusions: 1) lower educated characters are more dominant in dyadic conflicts and 2) the majority of triadic conflicts exist in a state of social balance.

Actual Fictions

“…Taking their cue from insights in the field of social network analysis, literary scholars in the 2000s and 2010s have increasingly started to transpose these methods and techniques to the analysis of fictional worlds (e.g. Alberich, Miro-Julia & Rossello 2002;Stiller et al 2003;Elson, Dames & McKeown 2010;Lee & Yeung 2012;Jayannavar Agarwal, Ju & Rambow 2015;Lee & Wong 2016;Grayson, Wade, Meaney & Greene 2016;Smeets 2021). But although it might seem just a small step from networks of people to networks of fictional characters, the phenomenon of character network analysis has brought along various practical and theoretical issues.…”

“…In Section 2, I will compare a sample of network data from the Dutch population with a sample of character network data from Dutch literary fiction in the same period. Before doing so, I will first describe various computational techniques that can be used to extract character networks from literary texts and provide some arguments for the technique I developed earlier (Smeets 2021) Inspired by the two extremes to the debate on mimesis, I will take the following two hypotheses as points of departure:…”

“…Based on the co-occurrence of characters at the sentence level (Smeets et al 2019), I developed a technique to semiautomatically extract social networks of the fictional characters from each of the novels in the corpus. 28 This approach is semiautomatic in the sense that it uses automatic named entity recognition to detect characters and their name variants ("Frits," "Frits van Egters," "Van Egters"), 29 after which errors are manually corrected for each individual novel.…”

“…For instance, if a novel in the corpus has a gender assortativity coefficient of 1, then this novel only features same-sex relations (man-man, woman-woman) whereas a score of -1 means that this novel contains only opposite-sex relations (man-woman, woman-man). Thus, a gender assortativity of 1 means that the 30 For more information on the data collection in the various research stages, see Smeets (2021). 31 For an elaboration on experiments with different window units and sizes, see Smeets (2021).…”

“…Both sections are grounded in the approach to character network analysis as presented in my book Character Constellations (2021). Based on the co-occurrence of characters on the sentence level (Smeets et al 2019), it semi-automatically extracts social networks of fictional characters from contemporary literary texts written in the Dutch language. 15 This method for extracting character networks allows for an exploration of the two research questions in light of the long-standing discussion on mimesis and realistic literary representation.…”