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

被引:3
作者
Mahapatra, Rupkumar [1 ]
Samanta, Sovan [2 ,3 ,4 ,5 ]
Pal, Madhumangal [1 ,6 ]
Allahviranloo, Tofigh [4 ,7 ]
Kalampakas, Antonios [8 ]
机构
[1] Vidyasagar Univ, Dept Appl Math, Midnapore 721102, West Bengal, India
[2] Western Caspian Univ, Dept Tech Sci, AZ-1001 Baku, Azerbaijan
[3] Tamralipta Mahavidyalaya, Dept Math, Tamluk 721636, West Bengal, India
[4] Istinye Univ, Res Ctr Performance & Prod Anal, TR-34396 Istanbul, Turkiye
[5] Algebra Univ, Dept Tech Sci, Gradiscanska 24, Zagreb 10000, Croatia
[6] Saveetha Inst Med & Tech Sci, Saveetha Sch Engn, Dept Math & Innovat, Chennai 602105, Tamilnadu, India
[7] Islamic Azad Univ, Quantum Technol Res Ctr QTRC, Sci & Res Branch, Tehran 1477893855, Iran
[8] Amer Univ Middle East, Coll Engn & Technol, Egaila 54200, Kuwait
关键词
linguistic Z-graphs; fuzzy graphs; influential nodes; social networks; centrality measure; LINK PREDICTION; FUZZY;
D O I
10.3390/math12182898
中图分类号
O1 [数学];
学科分类号
0701 ; 070101 ;
摘要
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.
引用
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页数:24
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