Computational hermeneutics of emotion: a comparative study of emotional landscapes in the Dostoevsky’s novel “Crime and Punishment”

Abstract This study employs computational hermeneutics to explore emotional representations in Fyodor Dostoevsky’s Crime and Punishment . Using advanced Natural Language Processing (NLP) techniques, including sentiment analysis powered by the BERT model and other tools, we examine the emotional and existential aspects embedded in the narrative. Our approach combines computational tools with traditional hermeneutic methods to deconstruct the emotional journey of the protagonist, Rodion Raskolnikov. We quantitatively analyze his emotional evolution before and after the pivotal crime, mapping his psychological transition from detachment to engagement. The study focuses on four key emotional dimensions: Attitude, Introspection, Sensitivity, and Temper. By transforming qualitative textual data into a quantitative framework, we provide a novel illustration of Raskolnikov’s psychological progression from a state of depersonalization to full emotional contact. This computational analysis is contextualized within a broader philosophical interpretation, drawing on concepts such as Stoic apatheia and Heideggerian Sorge . Our research serves a dual purpose: it enhances our understanding of Dostoevsky’s work while demonstrating the potential of computational methods in literary analysis. By bridging digital humanities and traditional literary criticism, this study contributes to the growing field of digital hermeneutics and opens new avenues for interdisciplinary research in literature, philosophy, and computational linguistics.

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Publication Details

Journal
Humanities and Social Sciences Communications
Published
2024-10-26
DOI
https://doi.org/10.1057/s41599-024-03955-w
Citations
2
Primary Topic
Language, Metaphor, and Cognition
Type
article
Field-Weighted Citation Impact
1.02
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article

Computational hermeneutics of emotion: a comparative study of emotional landscapes in the Dostoevsky’s novel “Crime and Punishment”

Davide Picca, Alberto Romele, Antonin Schnyder
2 citations
Humanities and Social Sciences Communications
Language, Metaphor, and Cognition
1.02
article

Computational hermeneutics of emotion: a comparative study of emotional landscapes in the Dostoevsky’s novel “Crime and Punishment”

Davide Picca, Alberto Romele, Antonin Schnyder
article en
2 citations

Abstract

Abstract This study employs computational hermeneutics to explore emotional representations in Fyodor Dostoevsky’s Crime and Punishment . Using advanced Natural Language Processing (NLP) techniques, including sentiment analysis powered by the BERT model and other tools, we examine the emotional and existential aspects embedded in the narrative. Our approach combines computational tools with traditional hermeneutic methods to deconstruct the emotional journey of the protagonist, Rodion Raskolnikov. We quantitatively analyze his emotional evolution before and after the pivotal crime, mapping his psychological transition from detachment to engagement. The study focuses on four key emotional dimensions: Attitude, Introspection, Sensitivity, and Temper. By transforming qualitative textual data into a quantitative framework, we provide a novel illustration of Raskolnikov’s psychological progression from a state of depersonalization to full emotional contact. This computational analysis is contextualized within a broader philosophical interpretation, drawing on concepts such as Stoic apatheia and Heideggerian Sorge . Our research serves a dual purpose: it enhances our understanding of Dostoevsky’s work while demonstrating the potential of computational methods in literary analysis. By bridging digital humanities and traditional literary criticism, this study contributes to the growing field of digital hermeneutics and opens new avenues for interdisciplinary research in literature, philosophy, and computational linguistics.

Humanities and Social Sciences CommunicationsVol. 11(1)
Université Sorbonne Nouvelle (FR), University of Lausanne (CH)
Openalex Percentile: Top 21%
Language, Metaphor, and Cognition
1.02
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