Next Gen Text Mining in English Literature: A Machine Learning Approach for Narrative and Stylistic Analysis

Title

Next Gen Text Mining in English Literature: A Machine Learning Approach for Narrative and Stylistic Analysis

Creator

Jiby Jose, E.; Biswas, Priyanka

Description

This paper presents a research work that is novel in nature, based on a new machine learning framework that focuses on a computational analysis in the field of English literature. This research uniquely aims at focusing on an intersection based on stylistic patterns and narrative structures. The newly proposed model is termed the 'Next Gen Text Mining Framework', which leverages transformer-based models (such as GPT, BERT), along with sentiment trajectory-based modeling, network analysis, and clustering algorithms for extracting stylistic features and latent semantics from the text on a large scale. A meticulously used re-processing type pipelining framework modifies and prepares the data for the model ingestion. The multi-modal approach used in this framework enables the experimental analysis of different models across various diverse corpora in the literature that demonstrate stability, superior accuracy, and robustness when compared to the traditional models, in tasks like the authorship attribution, sentimental trajectory mapping, and the theme-based classification. The proposed framework bridges the gap between distant and close reading practices, enhancing the pedagogically based engagements and translating the computational insights into interpretative forms for research and teaching. This research highlights a scalable and replicable framework model that is a transformative tool when a large-scale inquiry in literature is considered and sets a foundation towards multi-modal, future, cross-lingual, and multidisciplinary-based applications. 2025 IEEE.

Source

2025 IEEE 5th International Conference on ICT in Business Industry and Government, ICTBIG 2025;

Date

01-01-2025

Publisher

Institute of Electrical and Electronics Engineers Inc.

Subject

Computational Literary Studies; Machine Learning; Narrative Analysis; Stylistic Analysis; Text Mining; Transformer Models

Coverage

Jiby Jose E., CHRIST (Deemed to Be University), Bangalore, India; Biswas P., CHRIST (Deemed to Be University), Bangalore, India

Rights

Restricted Access; Hardcopy may be available in the library

Relation

ISBN: 979-833157981-4;

Format

online

Language

English

Type

Conference paper

Identifier

https://doi.org/10.1109/ICTBIG68706.2025.11323969

https://www.scopus.com/pages/publications/105032841648?origin=resultslist