Thematic Analysis and Visualization of Textual Corpus

TL;DR

This paper presents a method for thematic analysis and visualization of textual corpora by examining theme relevance variation, identifying thematic relations, and enabling thematic navigation for improved information exploration.

Contribution

It introduces a novel approach to analyze theme relevance variation and thematic associations, facilitating thematic path generation for better corpus exploration.

Findings

Identified major and minor themes within texts.

Mapped thematic association relations.

Enabled thematic navigation in information systems.

Abstract

The semantic analysis of documents is a domain of intense research at present. The works in this domain can take several directions and touch several levels of granularity. In the present work we are exactly interested in the thematic analysis of the textual documents. In our approach, we suggest studying the variation of the theme relevance within a text to identify the major theme and all the minor themes evoked in the text. This allows us at the second level of analysis to identify the relations of thematic associations in a textual corpus. Through the identification and the analysis of these association relations we suggest generating thematic paths allowing users, within the frame work of information search system, to explore the corpus according to their themes of interest and to discover new knowledge by navigating in the thematic association relations.