In the critique of literary representation, the depiction of literary characters has been studied from ideological perspectives. Hierarchies can be exposed by determining the centrality of a character relative to other characters. As an addition to such close reading methods, the present paper proposes an approach to character centrality that combines network analysis with narratology. This explorative study is based on a dataset of demographic metadata on 2,137 characters from a corpus of 170 contemporary Dutch novels. We extract social networks of characters from each novel, and rank all characters according to five centrality metrics. Then, we perform a multiple linear regression to test which of the demographic variables predicts a character’s position in the rankings. Our results suggest that immigrant and female characters score higher on two of the five centrality metrics. As a narratological evaluation, we contextualise this observed pattern in relation to a close reading of Özcan Akyol’s Eus (2012), a novel from the corpus that thematises both descent and gender. We demonstrate that our data-driven and empirically informed approach to character centrality lays bare surprising patterns of representation which only gain relevance in light of close readings of specific cases.