We study whether patterns of segregation and homogeneity in personal networks in the Netherlands are comparable to the network structures of characters in modern Dutch literature and examine the degree to which social divides in terms of sex, education, ethnicity, and age are reflected in literary novels. A representative sample of people living in the Netherlands (the Survey of the Social Networks of the Dutch, SSND 2014, n = 967 respondents and 3424 network members) is employed as well as a representative sample from Dutch literary fiction published in 2012 and submitted to the Libris Prize (n = 170 books and 1292 characters). While controlling for author characteristics, our multilevel regression models reveal that networks in books are more diverse in terms of ethnicity, education and age. However, higher levels of education show more closure in books than in the actual world, and the same holds for characters with a higher age. We conclude with a discussion of the relationship between literature and society. IntroductionIn Dutch society, like in other modern western societies, severe social divides constitute challenges for the future. These are the divides according to differences in educational levels, ethnic background, age, and sex. People with different backgrounds in these regards are out of each other's sight and they have only little contact with each other. As a result, their networks do not overlap, and the social worlds of different groups are largely separated. In social science, divides are studied as patterns of social segregation and homogeneity in networks and it is argued that strong patterns of segregation hamper intergroup solidarity and diminish social cohesion (e.g. Briggs, 2001;Markovsky & Lawler, 1994;Pettigrew, 1998). Importantly, if social divides recur in cultural domains, such as in fiction writing, social cohesion is probably even more threatened than actually thought, because the actually existing divides are not even bridged in the imagined social structures. Hence, the degree of network segregation in fiction writing can be perceived as an additional indicator of the strength of segregation and divides in the actual world.This paper examines this issue and studies the question whether network patterns with regard to homogeneity and segregation of characters in books reflect network patterns of people in the Netherlands. Much research shows that people's networks are considerable homogenously composed in terms of important social background characteristics such as age, race, education, and sex. How is this in contemporary fiction writing? Is it likely that two befriended characters in a novel differ in ethnic background and/or education? And how likely is it that friends in a novel diverge in age? We employ two sets of data, a national representative dataset on

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.

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Fiction has a major social impact, not least because it co-shapes the image that society has of various social groups. Drawing on a collection of 170 contemporary Dutch-language novels, Character Constellations presents a range of data-driven, statistical models to study depictions of characters in terms of gender, race, ethnicity, class, age, sexuality, and other identity categories. Incorporating the tools of network analysis, each chapter highlights an aspect of fictional social networks that affects the representation of social groups: their centrality, their communities, and their conflicts. While reading individual novels in light of emerging statistical patterns, combining the formal methods of social network analysis with the interpretive tools of narratology, this study shows how central societal themes such as (in)equality and emancipation, integration and segregation, and social mobility and class struggle are foregrounded, replicated, or distorted in the Dutch novel. Showcasing what character-based critiques of literary representation gain by integrating data-driven methods into the practice of critical close reading, Character Constellations contributes to societal debates on cultural representation and identity and the role fiction and art have in those debates.