Modelling Conflicts Between Characters in Present-Day Dutch Literary Fiction.

Critiques of literary representation

Literary studies has a long tradition of analysing texts from an ideological perspective. Inspired by feminist (Butler 1990), postcolonial (Said 1978) and Marxist (Eagleton 1976) strands of thinking, these so called critiques of literary representation have been focusing on hierarchies between genders, ethnicities, and classes in literary texts. One way in which these hierarchies can be traced is through comparatively analysing representations of characters with different demographic backgrounds. For the field of Dutch literature, a diverse range of detailed close readings have been conducted analysing the relative importance of certain represented identities as opposed to others (Pattynama 1994, Meijer 1996a, Meijer 1996b, Pattynama 1998, Minnaard 2010, Meijer 2011).

In recent years, quantitative methods such as social network analysis have made it possible to study character representation on a larger scale (Alberich e.a. 2002, Stiller et al 2003, Elson et al 2010, Lee & Yeung 2012, Karsdorp et al 2012, Agarwal et al 2013, Jayannavar et al 2015, Karsdorp et al. 2015, Lee & Wong 2016, Van der Deijl & Smeets 2018). Insights from e.g. network theory can lead to a broader understanding of the power dynamics between characters. Important aspects of these dynamics are positive (friends) and negative (enemies) relations between characters, as bonds and conflicts in networks are indicative of hierarchical oppositions between represented identities.
In order to gain an empirically informed understanding of character hierarchies in present-day Dutch literary fiction, the present paper models conflicts for all 2137 characters in a corpus of 170 novels that were submitted to one year (2012) of the Libris Literatuurprijs, one of the most prestigious literary prizes in the Dutch language area. It draws on extensive metadata from earlier research in which gender, descent, age, education and profession of all these characters were gathered (Van der Deijl, Pieterse, Prinse, Smeets 2016), as well on more recent research in which relational information (family, lover, colleague, friend, enemy) between these characters was collected (Volker & Smeets 2018).

Methodological design
Social networks for each of the 170 novels are semi-automatically extracted using the co-occurrence approach described in Smeets & Sanders 2018. These networks are used to model conflicts in two ways, the first of which focuses on conflicts between two characters (dyads), the second on conflicts between three characters (triads).

Conflict scores

In earlier research (Smeets et al 2018), all characters were ranked with Python’s NetworkX library (Hagberg et al 2008) for five basic network centrality metrics: degree, betweenness, closeness, eigenvector, and Katz. Each of these rankings are an indication of a certain aspect of a character’s relative importance in the story. For every dyad of enemies in the corpus, it is detected who the higher ranked character is. For each of the five centrality metrics, a character’s

conflict score
is incremented by 1 in case he/she is higher ranked than his enemy.

Finally, a multiple linear regression analysis is carried out to test the extent to which a character’s gender, descent, age or education is a predictor of his/her conflict score. The outcome of the regression analysis serves as an indicator of which represented identities are the more powerful ones in the conflict.

Social (im)balance

The social balance theory (Heider 1946) postulates that there is
social balance
in a triad when either all three nodes are friends, or when two friends share the same enemy. Conversely, it postulates that there is
social imbalance
when all three nodes are enemies, or when two enemies share the same friend. This is used as a theoretical framework for modelling conflict dynamics between subnetworks of three characters in the corpus.

For every enemy/friend triad, it is automatically established whether it is socially balanced or imbalanced according to the theory. It turns out that the majority of triads, 69%, is socially balanced as opposed to 31% of socially imbalanced triads. Among these two general categories of social balance and imbalance, fully positive and fully negative triads are most present (see Figure 1 for the absolute distributions per type). In light of authoritative narratological theories (Propp 1928, Greimas 1966), the prevalence of social balance is remarkable, as conflict is commonly esteemed to be one of the driving forces behind narrative action.

For the analysis of conflicts in individual novels, this observed pattern can be used as a general framework to contextualise and evaluate the particularity of (im)balanced triadic subnetworks. One such a contextualisation will be demonstrated by evaluating a single triad in light of the overall pattern.

Figure 1. Absolute distribution of social (im)balance for all enemy/friend-triads in the corpus divided by type (N =1059)

Contribution to the field

In this paper the two models of conflict will be used to disentangle the complexities of power dynamics in character representation. We will assess the possibilities and challenges of our approach for critiques of literary representation that mainly use qualitative close reading methods. It will be argued that conflict situations co-shape the ideological representation of characters in literature, and the importance of a data-driven and empirically informed approach to character representation will be highlighted. .

Keywords:
conflict,
social network analysis, Digital Literary Studies, Dutch literature

Bibliography

Agarwal et al 2013 – A. Agarwal e.a., ‘Automatic Extraction of Social Networks from Literary Text:
A Case Study on Alice in Wonderland’. Online, 2013.

http://www.cs.columbia.edu/~apoorv/Homepage/Publications_files/MAIN.pdf

Alberich et al 2002 – R. Alberich e.a., ‘Marvel Universe looks almost like a real social network.’ Online, 2002.

https://arxiv.org/abs/cond-mat/0202174v1

Butler 1990 – Butler, Judith.
Gender Trouble. USA (Routledge): 1990.

Deijl, van der & Smeets 2018 – L. van der Deijl & Roel Smeets, ‘Tussen close en distant. Personage-hiërarchieën in Peter Buwalda’s
Bonita Avenue’. In:
Tijdschrift voor Nederlandse Taal- en Letterkunde 134 (2018) 2, p.123-145

Eagleton 1976 – T. Eagleton,
Marxism and Literary Criticism. USA (Routledge): 1976.

Elson et al 2010 – D.K. Elson e.a., ‘Extracting Social Networks from Literary Fiction 2010’. In:
Proceedings of the 48th Annual Meeting of the Association for Computational Linguistics (2010), p. 138–147.

Greimas 1966 – A.J. Greimas,
Sémantique structurale, Paris: Presse universitaires de France, 1966.

Hagberg et al 2008 – Aric A. Hagberg, Daniel A. Schult and Pieter J. Swart, “Exploring network structure, dynamics, and function using NetworkX”, in Proceedings of the 7th Python in Science Conference (SciPy2008), Gäel Varoquaux, Travis Vaught, and Jarrod Millman (Eds), (Pasadena, CA USA), pp. 11–15, Aug 2008

Heider 1946 – Fritz Heider, ‘Attitudes and Cognitive Organization’, In: The Journal of Psychology 21 (1946), pp. 107-112

Jayannavar et al
2015 – P. Jayannavar e.a., ‘Validating literary theories using automatic social network extraction’. In:
Proceedings of the Fourth Workshop on Computational Linguistics for Literature
(2015), p.32-41.

Karsdorp et al 2012 – Folgert Karsdorp, Peter van Kranenburg, Theo Meder, Antal van den Bosch ‘Casting a spell: Identification and ranking of actors in folktales.’ In: F. Mambrini, M. Passarotti, and C. Sporleder (eds.),
Proceedings of the Second Workshop on Annotation of Corpora for Research in the Humanities (ACRH-2), 2012, p. 39–50.

Karsdorp et al 2015. – Folgert Karsdorp, Mike Kestemont, Christof Schöch, Antal van den Bosch. ‘The ‘Love Equation: Computational Modeling of Romantic Relationships in French Classical Drama.’ In:
Proceedings of the Sixth International Workshop on Computational Models of Narrative, 2015, pp. 98-107.

Lee & Yeung 2012 – J. Lee & C.Y. Yeung, ‘Extracting Networks of People and Places from Literary Texts’. In:
Proceedings of the 26th Pacific Asia Conference on Language, Information and Computation 2012 (2012), p.209-218.

Lee & Wong 2016 – J. Lee & T.S. Wong, ‘Hierarchy of Characters in the Chinese Buddhist Canon’. In
Proceedings of the Twenty-Ninth International Florida Artificial Intelligence Research Society Conference,(2016), p.531-534.

Meijer 1996a – M. Meijer, ‘De verschrikkelijke sneeuwman: projectie, geweld en nieuwe mannelijkheid in het werk van Jan Wolkers’. In:
Het omstreden slachtoffer: geweld van vrouwen en mannen. Ed. R. Romkens & S. Dijkstra. Baarn: Ambo, 1996, p 39-58.

Meijer 1996b – M. Meijer,
In tekst gevat. Inleiding tot de kritiek van de representatie. Amsterdam: Amsterdam University Press, 1996.

Meijer 2011 – M. Meijer, ‘Zwartheid in de witte verbeelding’. In: Judit Gera et al. (red.), Diversiteit, Boedapest (Printart Press Kft.): 2011, p.47-74.

Minnaard 2010 – L. Minnaard, ‘The Spectacle of an Intercultural Love Affair. Exoticm in Van Deyssel’s Blank en Geel.’ In:
Journal of Dutch Literature 1 (2010) 1, p. 74-90.

Pattynama 1994 – P. Pattynama, ‘Oorden en woorden. Over rassenvermenging, interetniciteit, en een Indisch meisje.’ In:
Tijdschrift voor Vrouwenstudies 15 (1994) 1, pp. 30-45.

Pattynama 1988 – P. Pattynama. ‘Secrets and Danger: Interracial Sexuality in Louis Couperus’s
The Hidden Force and Dutch Colonial Culture around 1900’. In: J. Clancy-Smith & F. Gouda,
Domesticating the Empire. Race, Gender, and Family Life in French and Dutch Colonialism. Charlottesville/London: University Press of Virginia, 1998, p. 84-107,

Propp 1928 – Vladimir Propp,
Morphology of the Folktale [2nd edition]. First edition translated by Laurence Scott with and introduction by Svatava Prokova-Jakobson, second edition revised and edited with a preface by Louis. A. Wagner and new introduction by Alan dudes. Austin/London (University of Texas Press): 1968 [originally published in 1928]

Said 1978 – E. W. Said,
Orientalism. London (Vintage): 1978.

Smeets & Sanders 2018 – Smeets, R. & E. Sanders. ‘Character Centrality in Present-Day Dutch Literary Fiction.’ Long Paper at Digital Humanities Benelux, Amsterdam, 8-6-2018. Link.

Smeets et al 2018 – Smeets, R., Sanders, E. & A. van den Bosch. ‘Ranking Characters in Present-Day Dutch Literary Fiction.’ Under review in
DH Benelux Journal.

Stiller et al 2003 – J. Stiller e.a. ‘The Small World of Shakespeare's Plays.’ In:
Hum Nat 14 (2003) 4, p. 397-408.

Volker & Smeets 2018 – B. Volker & R. Smeets. ‘Mirrors or alternative worlds? Comparing ego centered networks of characters in contemporary Dutch literature with networks in the population’.
International Network of Social Network Analysis, Sunbelt Social Network Conference, June 2018, Utrecht. R&R in
Poetics.