References
- A. A Camacho, D., Panizo-LLedot, Á., Bello-Orgaz, G., Gonzalez-Pardo, A. & Cambria, E. The four dimensions of social network analysis: An overview of research methods, applications, and software tools. Inf. Fusion 63, 88–120 (2020).
- Zareie, A., Sheikhahmadi, A. & Jalili, M. Identification of influential users in social networks based on users’ interest. Inf. Sci. 493, 217–231 (2019).
- Al-Garadi, M. A. et al. Analysis of online social network connections for identification of influential users: Survey and open research issues. ACM Comput. Surv. (CSUR) 51(1), 1–37 (2018).
- Peng, S., Wang, G. & Xie, D. Social influence analysis in social networking big data: Opportunities and challenges. IEEE Netw. 31(1), 11–17 (2016).
- Zareie, A., Sheikhahmadi, A. & Jalili, M. Identification of influential users in social network using gray wolf optimization algorithm. Expert Syst. Appl. 142, 112971 (2020).
- Mohammadi, A. & Saraee, M. Finding influential users for different time bounds in social networks using multi-objective optimization. Swarm Evol. Comput. 40, 158–165 (2018).
- Saoud, B. & Moussaoui, A. Community detection in networks based on minimum spanning tree and modularity. Physica A 460, 230–234 (2016).
- Zhao, Y., Li, S. & Jin, F. Identification of influential nodes in social networks with community structure based on label propagation. Neurocomputing 210, 34–44 (2016).
- Vathi, E., Siolas, G. & Stafylopatis, A. Mining and categorizing interesting topics in twitter communities. J. Intell. Fuzzy Syst. 32(2), 1265–1275 (2017).
- Moosavi, S. A., Jalali, M., Misaghian, N., Shamshirband, S. & Anisi, M. H. Community detection in social networks using user frequent pattern mining. Knowl. Inf. Syst. 51(1), 159–186 (2017).
- Wang, M., Zuo, W. & Wang, Y. An improved density peaks-based clustering method for social circle discovery in social networks. Neurocomputing 179, 219–227 (2016).
- Hu, Y. & Yang, B. Enhanced link clustering with observations on ground truth to discover social circles. Knowl. Based Syst. 73, 227–235 (2015).
- Chen, M., Kuzmin, K. & Szymanski, B. K. Community detection via maximization of modularity and its variants. IEEE Trans. Comput. Soc. Syst. 1(1), 46–65 (2014).
- Lancichinetti, A., Fortunato, S. & Kertész, J. Detecting the overlapping and hierarchical community structure in complex networks. New J. Phys. 11(3), 033015 (2009).
- J. Zhang, D. Chen, Q. Dong, Z. Zhao Identifying a set of influential spreaders in complex networksSci. Rep., 6 (1) (2016), Article 27823
- S. Kumar, B. PandaIdentifying influential nodes in social networks: neighborhood coreness based voting approach Physica A, 553 (2020), Article 124215
- A. Ullah, B. Wang, J. Sheng, J. Long, N. Khan, Z. SunIdentification of nodes influence based on global structure model in complex networksSci. Rep., 11 (1) (2021), pp. 1-11
- H. Zhang, S. Zhong, Y. Deng, H.C. KangLFIC: identifying influential nodes in complex networks by local fuzzy information centralityIEEE Trans. Fuzzy Syst., 30 (8) (2021), pp. 3284-3296
- F. Yang, R. Zhang, Z. Yang, R. Hu, M. Li, Y. Yuan, K. LiIdentifying the most influential spreaders in complex networks by an extended local K-shell sumInt. J. Mod. Phys. C, 28 (1) (2017), Article 1750014
- H. Sun, D. Chen, J. He, E. Ch’ngA voting approach to uncover multiple influential spreaders on weighted networksPhysica A, 519 (2019), pp. 303-312
- L. Li, S. Fang, Y. YaoIdentifying influential nodes in social networks: a voting approachChaos, Solit. Fractals, 152 (2021), Article 111309