Abstract
The paper presents a scalable and generalized approach to social network analysis using fuzzy graph theory. It proposes an intelligent sociocentric approach that calculates the degree of potential relationship of a social network of finite size by proposing a fuzzy graph social network model. It takes into account social entity functional and relational attributes simultaneously. It computes the degree of potential relationship of a social network in two steps. The first step computes the fuzzy pairwise relationship between all social nodes or entities by incorporating the proposed fuzzy node activeness index parameter with an online and offline communication relationship. The second step further uses all fuzzy pairwise relationships calculated in the first step to calculate the degree of potential relationship of a social network. It uses an astute function that utilizes weighted arithmetic and geometric means of the relationships between entities. It also uses two weights—betweenness and closeness centrality of an entity in the social network. The paper performs the experimental work on a small WhatsApp social network of undergraduate students in the university for 6 months. Hence, the paper proposes the degree of potential relationship in social networks, which may be used as a global parameter to compare different social networks by simultaneously incorporating social node's functional and relational attributes.
This is a preview of subscription content, log in via an institution to check access.
Similar content being viewed by others
Data availability
Enquiries about data availability should be directed to the authors.
References
Al-Zoubi M, Al-Dahoud M, Al-Akhras M (2010) An efficient fuzzy K-medoids method. World Appl Sci 10:574–583
Bastian M, Heymann S, Jacomy M (2009) Gephi: an open source software for exploring and manipulating networks. In: Third international AAAI conference on weblogs and social media, pp 361–362
Bouarara HA (2021) Recurrent neural network (RNN) to analyse mental behaviour in social media. Int J Softw Sci Comput Intell 13:1–11. https://doi.org/10.4018/ijssci.2021070101
Brunelli M, Fedrizzi M (2009) A fuzzy approach to social network analysis. In: International conference on advances in social network analysis and mining. IEEE, pp 225–240
Brunelli M, Fedrizzi M, Fedrizzi M (2009) OWA-based fuzzy m-ary adjacency relations in social network analysis. In: DISA
Brunelli M, Fedrizzi M, Fedrizzi M (2014) Fuzzy m-ary adjacency relations in social network analysis: Optimization and consensus evaluation. Inf Fusion 17:36–45
Clafferty EM (2011) Facilitating social networking within the student experience. Int J Electr Eng Educ 48:245–251. https://doi.org/10.7227/IJEEE.48.3.3
Das K, Naseem U, Samanta S, Khan SK, De K (2021) Fuzzy mixed graphs and its application to identification of COVID19 affected central regions in India. J Intell Fuzzy Syst 40:1051–1064. https://doi.org/10.3233/JIFS-201249
Faust K (2006) Comparing social networks: size, density, and local structure. Metod Zv 3:185–216
Freeman LC (1977) A set of measures of centrality based on betweenness. Sociometry 40:35–41
Freeman LC (1978) Centrality in social networks conceptual clarification. Soc Netw 1:215–239. https://doi.org/10.1016/0378-8733(78)90021-7
Hanneman RA, Riddle M, Robert A (2005) Introduction to social network methods. University of California Riverside, Riverside
Ishikawa S, Kikuchi K (2021) Quantum fuzzy logic and time. J Appl Math Phys 09:2609–2622. https://doi.org/10.4236/jamp.2021.911168
Jackson MO (2010) Social and economic networks. Princeton University Press, Princeton
Johnson R, Kovacs B, Vicsek A (2012) A comparison of email networks and off-line social networks: a study of a medium-sized bank. Soc Netw 34:462–469
Koam ANA, Akram M, Liu P (2020) Decision-making analysis based on fuzzy graph structures. Math Probl Eng 2020:1–30. https://doi.org/10.1155/2020/6846257
Koczy L (1992) Fuzzy graphs in the evaluation and optimization of networks. Fuzzy Sets Syst 46:307–319
Lippold T, Burns J (2009) Social support and intellectual disabilities: a comparison between social networks of adults with intellectual disability and those with physical disability. J Intellect Disabil Res 53:463–473. https://doi.org/10.1111/j.1365-2788.2009.01170.x
Malek S, Golsefid M, Hossien M, Zarandi F (2015) Fuzzy community detection model in social networks. Int J Intell Syst 43:1227–1244. https://doi.org/10.1002/int.21743
Murugesan S (2007) Understanding Web 2.0. IT Prof 9:34–41. https://doi.org/10.1109/MITP.2007.78
Musiał K, Kazienko P (2013) Social networks on the Internet. World Wide Web 16:31–72. https://doi.org/10.1007/s11280-011-0155-z
Nădăban S (2021) From classical logic to fuzzy logic and quantum logic: a general view. Int J Comput Commun Control 16:1–14. https://doi.org/10.15837/ijccc.2021.1.4125
Noor S, Guo Y, Shah SHH, Nawaz MS, Butt AS (2020) Research synthesis and thematic analysis of twitter through bibliometric analysis. Int J Semant Web Inf Syst 16:88–109. https://doi.org/10.4018/IJSWIS.2020070106
Perkins SE, Cagnacci F, Stradiotto A, Arnoldi D, Hudson PJ (2009) Comparison of social networks derived from ecological data: Implications for inferring infectious disease dynamics. J Anim Ecol 78:1015–1022. https://doi.org/10.1111/j.1365-2656.2009.01557.x
Rani P, Shokeen J (2021) A survey of tools for social network analysis. Int J Web Eng Technol 16:189–216. https://doi.org/10.1504/IJWET.2021.119879
Rani P, Bhatia M, Tayal DK (2018a) Qualitative SNA methodology. In: Proceedings of the 12th INDIACom and 5th international conference on computing for sustainable global development
Rani P, Bhatia MPS, Tayal DK (2018b) An astute SNA with OWA operator to compare the social networks. Int J Inf Technol Comput Sci 3:71–80. https://doi.org/10.5815/ijitcs.2018.03.08
Rani P, Bhatia MPS, Tayal DK (2018c) Qualitative SNA Methodology. In: 5th International conference on computing for sustainable global development. IEEE, pp 4223–4228
Rani P, Bhatia MPS, Tayal DK (2018d) A soft-computing based approach to Group relationship analysis using weighted arithmetic and geometric mean. In: International conference on innovative computing and communication. Springer, Berlin, pp 171–178
Rani P, Tayal DK, Bhatia MPS (2018e) Different aspects, challenges, and impact of social networks with a mathematical analysis of teaching learning process. J Adv Res Dyn Control Syst 14:1576–1590
Rani P, Bhatia MPS, Tayal DK (2019a) A comparative study of qualitative and quantitative SNA. In: 6th international conference on computing for sustainable global development. IEEE, pp 500–504
Rani P, Bhatia MPS, Tayal DK (2019b) Predicting facebook group relationship. Int J Innov Technol Explor Eng 8:1862–1869
Rani P, Tayal DK, Bhatia MPS (2019c) SNA using user experience. In: International conference on machine learning, big data, cloud and parallel computing: trends, perspectives and prospects. IEEE, pp 125–128
Rani P, Bhatia MPS, Tayal DK (2021) Conical SNA using Fuzzy K-Medoids based on user experience. Int J Electr Eng Educ. https://doi.org/10.1177/0020720920988490
Reiser R, Lemke A, Avila A, Vieira J, Pilla M, Du Bois A (2016) Interpretations on quantum fuzzy computing: intuitionistic fuzzy operations × quantum operators. Electron Notes Theor Comput Sci 324:135–150. https://doi.org/10.1016/j.entcs.2016.09.012
Rosenfeld A (1975) Fuzzy graphs. In: Zadeh LA, Fu KS, Shimura M (eds) Fuzzy sets and their applications. Academic Press, New York, pp 77–95
Sabzi A, Farjami Y, Zihayat M (2011) An improved fuzzy K-medoids clustering algorithm with optimized number of clusters. In: 11th international conference on hybrid intelligent systems, pp 206–210. https://doi.org/10.1109/HIS.2011.6122106
Sahoo SR, Gupta BB (2021) Multiple features based approach for automatic fake news detection on social networks using deep learning. Appl Soft Comput 100:106983. https://doi.org/10.1016/j.asoc.2020.106983
Samanta S (2014) A new approach to social networks based on fuzzy graphs. Turkish J Fuzzy Syst 5:78–99
Samanta S, Pal M (2013) Telecommunication system based on fuzzy graphs. J Telecommun Syst Manag 3:1–6. https://doi.org/10.4172/2167-0919.1000110
Schmitt I, Nürnberger A, Lehrack S (2009) On the relation between fuzzy and quantum logic. In: Seising R (ed) Studies in fuzziness and soft computing, pp 417–438
Sinthamani P (2021) An application of fuzzy graph in accidental prone zone to reduce the traffic congestion. Malaya J Mater 9:378–384. https://doi.org/10.26637/mjm0901/0063
Srinivasan S, Dhinesh Babu LD (2019) A parallel neural network approach for faster rumor identification in online social networks. Int J Semant Web Inf Syst 15:69–89. https://doi.org/10.4018/IJSWIS.2019100105
Wang C, Li X, Xu H, Li Z, Wang J, Yang Z, Mi Z, Liang X, Su T, Yang C, Wang G, Wang W, Li Y, Chen M, Li C, Linghu K, Han J (2022) Towards practical quantum computers : transmon qubit with a lifetime approaching 0. 5 milliseconds. Quantum Inf 8:1–6. https://doi.org/10.1038/s41534-021-00510-2
Wasserman S, Faust K (1994) Social network analysis: methods and applications, 8th edn. Cambridge University Press, Cambridge
Yager RR (2009) Intelligent social network modeling. In: IEEE/WIC/ACM Int Jt Conf Web Intell Intell Agent Technol, pp 8–8. https://doi.org/10.1109/WI-IAT.2009.373
Yager RR, Rochelle N (2008) Intelligent social network modeling and analysis. In: 3rd Int Conf Intell Syst Knowlede Enineering, pp 5–6. https://doi.org/10.1109/WI-IAT.2009.380
Yeboah J, Ewur GD (2014) The impact of whatsapp messenger usage on students performance in tertiary institutions in Ghana. J Educ Pract 5:157–164
Zadeh LA (1965) Fuzzy sets. Inf Control 8:338–353
Zhang Z, Sun R, Zhao C, Wang J, Chang CK, Gupta BB (2017) CyVOD: a novel trinity multimedia social network scheme. Multimed Tools Appl 76:18513–18529. https://doi.org/10.1007/s11042-016-4162-z
Acknowledgements
I would like to thank my guides Dr. M.P.S. Bhatia and Dr. Devendra K. Tayal for providing many helpful contributions during this paper.
Funding
The author declares no source of funding.
Author information
Authors and Affiliations
Corresponding author
Ethics declarations
Conflict of interest
The author declares no conflict of interest.
Informed consent
This research does not belong to any human participants or any welfare of animals.
Additional information
Communicated by Oscar Castillo.
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Rights and permissions
About this article
Cite this article
Rani, P., Tayal, D.K. & Bhatia, M.P.S. Sociocentric SNA on fuzzy graph social network model. Soft Comput 27, 13201–13216 (2023). https://doi.org/10.1007/s00500-022-06961-9
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s00500-022-06961-9