Sentiment Progression based Searching and Indexing of Literary Textual Artefacts

TL;DR

This paper introduces a sentiment progression-based indexing method for literary artefacts, enhancing search and recommendation systems by capturing emotional trajectories across texts, thus aligning better with reader interests and emotional experiences.

Contribution

The paper proposes a novel sentiment progression-based indexing approach for literary texts, incorporating emotional trajectories to improve search and personalized recommendations.

Findings

Sentiment progression clustering improves search relevance.

Database of 1076 English and 20 Marathi titles used for analysis.

Enhanced book recommendation based on emotional trajectories.

Abstract

Literary artefacts are generally indexed and searched based on titles, meta data and keywords over the years. This searching and indexing works well when user/reader already knows about that particular creative textual artefact or document. This indexing and search hardly takes into account interest and emotional makeup of readers and its mapping to books. When a person is looking for a literary textual artefact, he/she might be looking for not only information but also to seek the joy of reading. In case of literary artefacts, progression of emotions across the key events could prove to be the key for indexing and searching. In this paper, we establish clusters among literary artefacts based on computational relationships among sentiment progressions using intelligent text analysis. We have created a database of 1076 English titles + 20 Marathi titles and also used database http://www.cs.cmu.edu/~dbamman/booksummaries.html with 16559 titles and their summaries. We have proposed Sentiment Progression based Indexing for searching and recommending books. This can be used to create personalized clusters of book titles of interest to readers. The analysis clearly suggests better searching and indexing when we are targeting book lovers looking for a particular type of book or creative artefact. This indexing and searching can find many real-life applications for recommending books.