Volume 16 , Issue 1 , PP: 25-37, 2025 | Cite this article as | XML | Html | PDF | Full Length Article
Songa Venkata Rao 1 * , Bodapati Prajna 2
Doi: https://doi.org/10.54216/JCIM.160103
Numerous criteria are in place for social network applications. They require identification of network's core nodes. Traditional centrality measurements focus on specific node's direct connections or reachability. Often this disregards inherent ambiguity and complexity in real-world social networks. To address these constraints, we have introduced new method called Node Pack Fuzzy Information Centrality based on Pythagorean Neutrosophic Fuzzy Theory. Three essential values truth, falsity and indeterminacy have been added to this approach. This new approach provides a thorough depiction of social networks and it also offers a more sophisticated comprehension of connections between nodes. Complex and ambiguous interactions between entities can be effectively expressed using Pythagorean Neutrosophic values. Unlike traditional values, Pythagorean Neutrosophic values consider several uncertainty dimensions; this is a major improvement over traditional fuzzy value. Our approach handles relational complexity well and it includes self-weight for every node too. It represents each node's unique value, significance, or impact on the network. The network assessment is now more precise and contextual so we can assess centrality with greater precision. We applied this approach to a small academic network called university faculty/researchers. The application of Node Pack Fuzzy Information Centrality yielded promising results. It can enhance various activities associated with social network analysis. It can also offer valuable insights into the network architecture.
Centrality measures , Influential nodes , Node pack fuzzy information centrality , Pythagorean neutrosophic fuzzy graph , Social Networks
[1] L. A. Zadeh, "Fuzzy sets," Information and Control, vol. 8, pp. 338–353, 1965.
[2] Kauffman, Introduction à la Théorie des Sous-ensembles Flous, Masson et Cie Editeurs, Paris, 1973.
[3] K. Atanassov, "Intuitionistic fuzzy sets," Fuzzy Sets and Systems, vol. 20, pp. 87–96, 1986.
[4] R. R. Yager, "Pythagorean fuzzy subsets," in Proc. Joint IFSA World Congress and NAFIPS Annual Meeting, Edmonton, Canada, pp. 57–61, 2013.
[5] F. Smarandache, Neutrosophy neutrosophic probability, set, and logic, Amer. Res. Press, Rehoboth, USA, p. 105, 1998.
[6] Bavelas, "A mathematical model for group structures," Appl. Anthropol., vol. 7, pp. 16–30, 1948.
[7] Bavelas, "Communication patterns in task-oriented groups," J. Acoust. Soc. Am., vol. 22, pp. 725–730, 1950.
[8] Shimbel, "Structural parameters of communication networks," Bull. Math. Biophys., vol. 15, no. 4, pp. 501–507, 1953.
[9] L. Katz, "A new status index derived from sociometric analysis," Psychometrika, vol. 18, no. 1, pp. 39–43, 1953.
[10] J. Nieminen, "On the centrality in a graph," Scand. J. Psychol., vol. 15, pp. 322–336, 1974.
[11] L. C. Freeman, "Centrality in social networks: conceptual clarification," Soc. Netw., vol. 1, pp. 215–239, 1978.
[12] E. Estrada and J. A. Rodriguez-Velazquez, "Subgraph centrality in complex networks," Phys. Rev., vol. 71, p. 05610, 2005.
[13] P. Bonacich, "Some unique properties of eigenvector centrality," Soc. Netw., vol. 29, pp. 555–564, 2007.
[14] J. Bae and S. Kim, "Identifying and ranking influential spreaders in complex networks by neighborhood coreness," Physica A, vol. 395, pp. 549–559, 2014.
[15] J. Wang et al., "A novel weight neighborhood centrality algorithm for identifying influential spreaders in complex networks," Physica A, vol. 395, pp. 30121–30128, 2017.
[16] Y.-G. Zhang, R.-J. Hu, Q. Li, and W.-C. Ma, "Centrality measures in directed fuzzy social networks," Fuzzy Inf. Eng., vol. 7, no. 1, pp. 115–128, 2015.
[17] Q. Wang and Z. T. Gong, "Structural centrality in fuzzy social networks based on fuzzy hypergraph theory," Comput. Math. Organ. Theory, vol. 26, pp. 236–254, 2020.
[18] S. Samanta, V. K. Dubey, and B. Sarkar, "Measure of influences in social networks," Appl. Soft Comput., p. 106858, 2020, doi: 10.1016/j.asoc.2020.106858.
[19] Ajay et al., "Identifying influential nodes in directed weighted networks using Pythagorean fuzzy sets," J. Theor. Appl. Inf. Technol., vol. 101, no. 1, pp. 374–385, 2024.
[20] T. Zhou, L. Lu, Y. C. Zhang, and C. H. Yeung, "Leaders in social networks: the delicious case," PLoS ONE, vol. 6, no. 6, e21202, 2011, doi: 10.1371/journal.pone.0021202.
[21] M. Ling, M. Chuang, H. Zhang, and B. Wang, "Identifying influential spreaders in complex networks based on gravity formula," Physica A, vol. 451, pp. 205–212, 2016, doi: 10.1016/j.physa.2015.12.162.
[22] Q. Lu, Q. Li, and S. S. Liao, "A graph-based action network framework to identify prestigious members through member's prestige evolution," Decis. Support Syst., vol. 53, no. 1, pp. 44–54, 2012.
[23] P. Wang, J. Lu, and X. Yu, "Identification of important nodes in directed biological networks: a network motif approach," PLoS ONE, vol. 9, no. 8, e106132, 2014.
[24] J. Sheng, J. Dai, B. Wang, G. Duan, J. Long, J. Zhang, K. Guan, S. Hu, L. Chen, and W. Guan, "Identifying influential nodes in complex networks based on global and local structure," Physica A, vol. 541, p. 123262, 2020.
[25] X. Wang, W. Slamu, W. Guo, S. Wang, and Y. Ren, "A novel semi-local measure of identifying influential nodes in complex networks," Chaos Solitons Fractals, vol. 158, p. 112037, 2022.
[26] L. Panfeng, L. Li, F. Shiyu, and Y. Yukai, "Identifying influential nodes in social networks: a voting approach," Chaos Solitons Fractals, vol. 52, p. 111309, 2021.
[27] V. R. Songa and P. Bodapati, "Identifying influential nodes in directed weighted networks using Pythagorean fuzzy sets," J. Theor. Appl. Inf. Technol., vol. 101, no. 1, pp. 374–385, 2024.
[28] Ajay and P. Chellamani, "Pythagorean neutrosophic fuzzy graphs and their application in complex networks," Int. J. Comput. Intell. Appl., vol. 22, no. 4, pp. 278–289, 2023.
[29] M. E. Shaw, "Group structure and the behavior of individuals in small groups," J. Psychol., vol. 38, pp. 139–149, 1954.
[30] V. R. Songa and P. Bodapati, "Identifying influential nodes in directed weighted networks using Pythagorean fuzzy sets," J. Theor. Appl. Inf. Technol., vol. 101, no. 1, pp. 374–385, 2024.
[31] S. Brin and L. Page, "The anatomy of a large-scale hypertextual web search engine," Comput. Networks ISDN Syst., vol. 30, pp. 107–117, 1997.
[32] L. C. Freeman, "Centrality in social networks: conceptual clarification," Soc. Netw., vol. 1, pp. 215–239, 1978.
