I or Not I: Unraveling the Linguistic Echoes of Identity in Samuel Beckett's "Not I" Through Natural Language Processing
It provides insights for literary scholars and NLP researchers into Beckett's stylistic contributions, though it is incremental in applying existing NLP methods to a specific literary text.
This research tackled the analysis of Samuel Beckett's 'Not I' using natural language processing techniques like word frequency and BERT-based sentiment analysis, revealing how linguistic patterns reflect the protagonist's fragmented psyche and themes of time and existential angst.
Exploring the depths of Samuel Beckett's "Not I" through advanced natural language processing techniques, this research uncovers the intricate linguistic structures that underpin the text. By analyzing word frequency, detecting emotional sentiments with a BERT-based model, and examining repetitive motifs, we unveil how Beckett's minimalist yet complex language reflects the protagonist's fragmented psyche. Our results demonstrate that recurring themes of time, memory, and existential angst are artfully woven through recursive linguistic patterns and rhythmic repetition. This innovative approach not only deepens our understanding of Beckett's stylistic contributions but also highlights his unique role in modern literature, where language transcends simple communication to explore profound existential questions.