Analysis of Interrelations of Scientific Subject Areas Based on the Method of Graphosemantic Modeling

This article explores the unification of two relevant areas that are rarely studied together: the computational linguistics field of sentiment analysis and the physico-mathematical field of entropy-complexity. Based on keywords from articles on both topics, links are established that form a single s...

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Bibliographic Details
Published inAutomatic documentation and mathematical linguistics Vol. 59; no. 3; pp. 185 - 193
Main Authors Egorova, A. D., Amurskaya, O. Yu
Format Journal Article
LanguageEnglish
Published Moscow Pleiades Publishing 01.06.2025
Springer Nature B.V
Subjects
Complexity
Computer Science
Entropy
Information Analysis
Information Storage and Retrieval
Linguistics
Scientific visualization
Semantics
Sentiment analysis
NLP
sentiment analysis
computational linguistics
key words
information system “Semograph”
entropy-complexity
data visualization
machine learning
sentiment trajectories
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Summary:This article explores the unification of two relevant areas that are rarely studied together: the computational linguistics field of sentiment analysis and the physico-mathematical field of entropy-complexity. Based on keywords from articles on both topics, links are established that form a single semantic space at the junction of these subject areas. The information system of the data visualization tool Semograph was used to visualize the data and identify semantic links between semantic components and between sentiment analysis and entropy complexity.
Bibliography:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
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ISSN:0005-1055
1934-8371
DOI:10.3103/S0005105525700621