2026/05/28 by Julia Neugarten, Joris van Zundert · 1 voice
Computer Science · Psychology · #Authorship Attribution and Profiling #Emotions and Moral Behavior #Sentiment Analysis and Opinion Mining
paper · doi:10.1093/llc/fqag082
openalex publication_date 2026/05/28 · openalex created_date 2026/06/18 · openalex updated_date 2026/06/18
Abstract We present a computational analysis of the relationship between stylistic complexity and angry sentiment in Lale Gül’s novel Ik Ga Leven. We begin with the close-reading observation that, in this novel, the level of textual complexity increases when the narrator becomes angrier. This leads to the research questions: “What is the relationship between the level of complexity and the level of anger in this novel? Can this relationship be measured computationally?” To operationalize anger, we use a sentiment dictionary and a machine learning model fine-tuned on angry paragraphs. To operationalize textual complexity, we use Kolmogorov Complexity, a Dutch-language readability tool, and selected textual features. We contextualize the novel’s complexity by comparing it to the LitRiddle corpus of Dutch literature. The analysis indicates a relation between levels of anger and complexity in the novel. Our article thus illustrates the unusual position of Gül’s work in the contemporary Dutch literary landscape and illuminates the relationship between literary style and intradiegetic emotion, particularly anger. We also reflect on the uses and limitations of the tools, and on the challenge of combining sociocultural, stylistic, and content-level analysis of literature in computational literary studies. Finally, we identify some areas for future research.