Project Overview

Franz Kafka’s The Metamorphosis (1915) opens with one of the most arresting premises in literary history: Gregor Samsa awakens to find himself transformed into “some kind of monstrous vermin”. Yet what makes the novella truly unsettling is not the physical  transformation itself, but the gradual emotional dissolution that follows—Gregor’s slow alienation from his family, his work, and ultimately his own humanity. 

Kafka’s narrative has long invited interpretation through philosophical, psychoanalytic, and existentialist lenses. Scholars have examined it as a critique of modernity and enlightenment rationality, as a clinical portrait of psychic collapse under labor capitalism, and as an allegory of existential alienation. However, few studies have systematically traced the emotional trajectory of Gregor’s experience using computational methods. While traditional literary analysis offers rich interpretive frameworks, it rarely quantifies how sentiment shifts across the narrative’s three-part structure—from Gregor’s initial confusion, through his family’s escalating rejection, to his final resignation and death. 

This project addresses that gap by applying sentiment analysis—a computational technique that identifies and classifies emotions expressed in text—to The Metamorphosis. Using a pre-trained emotion classification model, the study tracks the protagonist’s emotional arc across the novella, identifying peaks in emotions such as disgust, sadness, fear, and neutral detachments. The goal is to produce a quantitative emotional map of Gregor’s experience that complements and enriches existing literary interpretations, while offering an accessible, feature-driven case study on the value of computational methods for literary analysis.