A Study on Linguistic Z-Graph and Its Application in Social Networks

This paper presents a comprehensive study of the linguistic Z-graph, which is a novel framework designed to analyze linguistic structures within social networks. By integrating concepts from graph theory and linguistics, the linguistic Z-graph provides a detailed understanding of language dynamics in online communities. This study highlights the practical applications of linguistic Z-graphs in identifying central nodes within social networks, which are crucial for online businesses in market capture and information dissemination. Traditional methods for identifying central nodes rely on direct connections, but social network connections often exhibit uncertainty. This paper focuses on using fuzzy theory, particularly linguistic Z-graphs, to address this uncertainty, offering more detailed insights compared to fuzzy graphs. Our study introduces a new centrality measure using linguistic Z-graphs, enhancing our understanding of social network structures.

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Publication Details

Journal
Mathematics
Published
2024-09-17
DOI
https://doi.org/10.3390/math12182898
Citations
28
Primary Topic
Caching and Content Delivery
Type
article
Field-Weighted Citation Impact
9.77
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article

A Study on Linguistic Z-Graph and Its Application in Social Networks

Antonios Kalampakas, Rupkumar Mahapatra, Madhumangal Pal, Sovan Samanta et al.
28 citations
Mathematics
Caching and Content Delivery
9.77
article

A Study on Linguistic Z-Graph and Its Application in Social Networks

Antonios Kalampakas, Rupkumar Mahapatra, Madhumangal Pal, Sovan Samanta, Tofigh Allahviranloo
article en
28 citations

Abstract

This paper presents a comprehensive study of the linguistic Z-graph, which is a novel framework designed to analyze linguistic structures within social networks. By integrating concepts from graph theory and linguistics, the linguistic Z-graph provides a detailed understanding of language dynamics in online communities. This study highlights the practical applications of linguistic Z-graphs in identifying central nodes within social networks, which are crucial for online businesses in market capture and information dissemination. Traditional methods for identifying central nodes rely on direct connections, but social network connections often exhibit uncertainty. This paper focuses on using fuzzy theory, particularly linguistic Z-graphs, to address this uncertainty, offering more detailed insights compared to fuzzy graphs. Our study introduces a new centrality measure using linguistic Z-graphs, enhancing our understanding of social network structures.

MathematicsVol. 12(18)
Islamic Azad University, Science and Research Branch (IR), American University of the Middle East (KW), Western Caspian University (AZ), Vidyasagar University (IN), Algebra Bernays University (HR), Istinye University (TR), Saveetha University (IN)
Quality Education
Openalex Percentile: Top 1%
Caching and Content Delivery
9.77
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A Study on Linguistic Z-Graph and Its Application in Social Networks — Antonios Kalampakas, Rupkumar Mahapatra, et al. · Mathematics (2024) | TGRS Research Map | TGRS