Abstract
This theoretical essay proposes an innovative interdisciplinary framework for literary analysis that integrates philosophy, psychology, and computational methods under the aegis of computational neurocognitive poetics. The proliferation of digital humanities has introduced tools such as sentiment analysis and topic modelling into literary studies, enabling the examination of large textual corpora with new precision. However, these quantitative approaches risk oversimplifying the complex, subjective nature of literary interpretation. This paper argues for bridging the gap between data-driven methods and humanistic inquiry by incorporating philosophical perspectives on meaning and authorship, alongside psychological insights into reader engagement. Furthermore, it addresses critical ethical concerns, particularly algorithmic bias, which can perpetuate social inequalities in literary analysis. By synthesizing computational techniques with philosophical and psychological frameworks, the study outlines a more comprehensive model that augments traditional literary criticism. The proposed framework suggests that computational methods, when rigorously contextualized within humanistic perspectives, can reveal intricate emotional patterns, cognitive dynamics, and thematic structures. This integrative approach not only enriches literary understanding but also promotes an ethically responsible and culturally inclusive analytical practice. Ultimately, this research charts a path for fruitful integration of digital tools with traditional methods, fostering interdisciplinary collaboration in literary studies.
Résumé
Cet essai théorique propose un cadre interdisciplinaire innovant pour l’analyse littéraire qui intègre la philosophie, la psychologie et les méthodes computationnelles sous l’égide de la poétique neurocognitive computationnelle. La prolifération des humanités numériques a introduit des outils tels que l’analyse des sentiments et la modélisation thématique dans les études littéraires, permettant l’examen de vastes corpus textuels avec une nouvelle précision. Cependant, ces approches quantitatives risquent de simplifier à l’excès la nature complexe et subjective de l’interprétation littéraire. Cet article plaide pour combler le fossé entre les méthodes fondées sur les données et la recherche humaniste en incorporant des perspectives philosophiques sur le sens et l’autorialité, ainsi que des insights psychologiques sur l’engagement du lecteur. En outre, il aborde des préoccupations éthiques cruciales, en particulier le biais algorithmique, qui peut perpétuer les inégalités sociales dans l’analyse littéraire. En synthétisant les techniques computationnelles avec des cadres philosophiques et psychologiques, l’étude esquisse un modèle plus complet qui augmente la critique littéraire traditionnelle. Le cadre proposé suggère que les méthodes computationnelles, lorsqu’elles sont rigoureusement contextualisées dans des perspectives humanistes, peuvent révéler des schémas émotionnels complexes, des dynamiques cognitives et des structures thématiques. Cette approche intégrative enrichit non seulement la compréhension littéraire, mais promeut également une pratique analytique éthiquement responsable et culturellement inclusive. En définitive, cette recherche trace une voie pour une intégration fructueuse des outils numériques avec les méthodes traditionnelles, favorisant la collaboration interdisciplinaire dans les études littéraires.
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