Cargando…

Social network analysis by Turiyam graphs

OBJECTIVE: A single valued neutrosophic set represented the uncertainty of real life situations in terms of membership [Formula: see text] , indeterminacy [Formula: see text] and non-membership [Formula: see text] degree. However, this uncertainty cannot be limited to those three degrees; there is a...

Descripción completa

Detalles Bibliográficos
Autores principales: Ganati, Gamachu Adugna, Repalle, V. N. Srinivasa Rao, Ashebo, Mamo Abebe
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10424366/
https://www.ncbi.nlm.nih.gov/pubmed/37580772
http://dx.doi.org/10.1186/s13104-023-06435-7
_version_ 1785089656519393280
author Ganati, Gamachu Adugna
Repalle, V. N. Srinivasa Rao
Ashebo, Mamo Abebe
author_facet Ganati, Gamachu Adugna
Repalle, V. N. Srinivasa Rao
Ashebo, Mamo Abebe
author_sort Ganati, Gamachu Adugna
collection PubMed
description OBJECTIVE: A single valued neutrosophic set represented the uncertainty of real life situations in terms of membership [Formula: see text] , indeterminacy [Formula: see text] and non-membership [Formula: see text] degree. However, this uncertainty cannot be limited to those three degrees; there is also an additional refusal degree. For this issue, the Turiyam set is an appropriate tool, which described the neutrosophic refusal degree of this situation as a liberal [Formula: see text] degree in addition to those three degrees. The graphical representation of this situation is required for knowledge processing. For this purpose, the Turiyam graph was introduced as an extension of the single valued neutrosophic graph. This graph is helpful when the depictions of the vertices or their relationships or both, are considered in terms of membership [Formula: see text] , indeterminacy [Formula: see text] , non-membership [Formula: see text] and liberal [Formula: see text] degrees. The goal of this paper is to introduce the degree, order and size in the context of Turiyam graphs and examine a social network (SN) with the help of this graph. RESULTS: In this regard, the degree, order and size in the context of Turiyam graphs are studied. The feasibility of this Turiyam graph is shown by employing its concept in a social network (SN). Finally, the advantage of the Turiyam graph over the existing graph theories is recognized by viewing its better framework.
format Online
Article
Text
id pubmed-10424366
institution National Center for Biotechnology Information
language English
publishDate 2023
publisher BioMed Central
record_format MEDLINE/PubMed
spelling pubmed-104243662023-08-15 Social network analysis by Turiyam graphs Ganati, Gamachu Adugna Repalle, V. N. Srinivasa Rao Ashebo, Mamo Abebe BMC Res Notes Research Note OBJECTIVE: A single valued neutrosophic set represented the uncertainty of real life situations in terms of membership [Formula: see text] , indeterminacy [Formula: see text] and non-membership [Formula: see text] degree. However, this uncertainty cannot be limited to those three degrees; there is also an additional refusal degree. For this issue, the Turiyam set is an appropriate tool, which described the neutrosophic refusal degree of this situation as a liberal [Formula: see text] degree in addition to those three degrees. The graphical representation of this situation is required for knowledge processing. For this purpose, the Turiyam graph was introduced as an extension of the single valued neutrosophic graph. This graph is helpful when the depictions of the vertices or their relationships or both, are considered in terms of membership [Formula: see text] , indeterminacy [Formula: see text] , non-membership [Formula: see text] and liberal [Formula: see text] degrees. The goal of this paper is to introduce the degree, order and size in the context of Turiyam graphs and examine a social network (SN) with the help of this graph. RESULTS: In this regard, the degree, order and size in the context of Turiyam graphs are studied. The feasibility of this Turiyam graph is shown by employing its concept in a social network (SN). Finally, the advantage of the Turiyam graph over the existing graph theories is recognized by viewing its better framework. BioMed Central 2023-08-14 /pmc/articles/PMC10424366/ /pubmed/37580772 http://dx.doi.org/10.1186/s13104-023-06435-7 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research Note
Ganati, Gamachu Adugna
Repalle, V. N. Srinivasa Rao
Ashebo, Mamo Abebe
Social network analysis by Turiyam graphs
title Social network analysis by Turiyam graphs
title_full Social network analysis by Turiyam graphs
title_fullStr Social network analysis by Turiyam graphs
title_full_unstemmed Social network analysis by Turiyam graphs
title_short Social network analysis by Turiyam graphs
title_sort social network analysis by turiyam graphs
topic Research Note
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10424366/
https://www.ncbi.nlm.nih.gov/pubmed/37580772
http://dx.doi.org/10.1186/s13104-023-06435-7
work_keys_str_mv AT ganatigamachuadugna socialnetworkanalysisbyturiyamgraphs
AT repallevnsrinivasarao socialnetworkanalysisbyturiyamgraphs
AT ashebomamoabebe socialnetworkanalysisbyturiyamgraphs