ILSHR Rumor Spreading Model by Combining SIHR and ILSR Models in Complex Networks

Full Text (PDF, 232KB), PP.51-59

Views: 0 Downloads: 0

Author(s)

Adel Angali 1 Musa Mojarad 2,* Hassan Arfaeinia 1

1. Department of Computer Engineering, Liyan Institute of Education, Bushehr, Iran

2. Department of Computer Engineering, Firoozabad Branch, Islamic Azad University, Firoozabad, Iran

* Corresponding author.

DOI: https://doi.org/10.5815/ijisa.2021.06.05

Received: 27 Jul. 2021 / Revised: 15 Sep. 2021 / Accepted: 12 Oct. 2021 / Published: 8 Dec. 2021

Index Terms

Complex networks, rumor spreading, SIHR model, ILSR model, ILSHR model

Abstract

Rumor is an important form of social interaction. However, spreading harmful rumors can have a significant negative impact on social welfare. Therefore, it is important to examine rumor models. Rumors are often defined as unconfirmed details or descriptions of public things, events, or issues that are made and promoted through various tools. In this paper, the Ignorant-Lurker-Spreader-Hibernator-Removal (ILSHR) rumor spreading model has been developed by combining the ILSR and SIHR epidemic models. In addition to the characteristics of the lurker group of ILSR, this model also considers the characteristics of the hibernator group of the SIHR model. Due to the complexity of the complex network structure, the state transition function for each node is defined based on their degree to make the proposed model more efficient. Numerical simulations have been performed to compare the ILSHR rumor spreading model with other similar models on the Sina Weibo dataset. The results show more effective ILSHR performance with 95.83% accuracy than CSRT and SIR-IM models.

Cite This Paper

Adel Angali, Musa Mojarad, Hassan Arfaeinia, "ILSHR Rumor Spreading Model by Combining SIHR and ILSR Models in Complex Networks", International Journal of Intelligent Systems and Applications(IJISA), Vol.13, No.6, pp.51-59, 2021. DOI: 10.5815/ijisa.2021.06.05

Reference

[1] Rezaeipanah, A., Ahmadi, G., & Matoori, S. S. (2020). A classification approach to link prediction in multiplex online ego-social networks. Social Network Analysis and Mining, 10(1), 1-16.
[2] Kosfeld, M. (2005). Rumours and markets. Journal of Mathematical Economics, 41(6), 646-664.
[3] Li, J., Jiang, H., Yu, Z., & Hu, C. (2019). Dynamical analysis of rumor spreading model in homogeneous complex networks. Applied Mathematics and Computation, 359, 374-385.
[4] Li, J., Jiang, H., Yu, Z., & Hu, C. (2019). Dynamical analysis of rumor spreading model in homogeneous complex networks. Applied Mathematics and Computation, 359, 374-385.
[5] Prathamesh Churi, N. T. Rao, " Teaching Cyber Security Course in the Classrooms of NMIMS University ", International Journal of Modern Education and Computer Science, Vol.13, No.4, pp. 1-15, 2021.
[6] Ma, C. (2017). Dynamical analysis of rumor spreading model with impulse vaccination and time delay. Physica A: Statistical Mechanics and its Applications, 471, 653-665.
[7] Cheng, Y. (2019). Dynamical analysis of a IWSR rumor spreading model with considering the self-growth mechanism and indiscernible degree. Physica A: Statistical Mechanics and its Applications, 536, 120940.
[8] Singh, J. (2019). A new analysis for fractional rumor spreading dynamical model in a social network with Mittag-Leffler law. Chaos: An Interdisciplinary Journal of Nonlinear Science, 29(1), 013137.
[9] Chen, G. (2019). ILSCR rumor spreading model to discuss the control of rumor spreading in emergency. Physica A: Statistical Mechanics and its Applications, 522, 88-97.
[10] Jiang, G., Li, S., & Li, M. (2020). Dynamic rumor spreading of public opinion reversal on Weibo based on a two-stage SPNR model. Physica A: Statistical Mechanics and its Applications, 558, 125005.
[11] Zhu, L., & Wang, B. (2020). Stability analysis of a SAIR rumor spreading model with control strategies in online social networks. Information Sciences, 526, 1-19.
[12] Yang, L., Li, Z., & Giua, A. (2020). Containment of rumor spread in complex social networks. Information Sciences, 506, 113-130.
[13] Islam, M. R., Liu, S., Wang, X., & Xu, G. (2020). Deep learning for misinformation detection on online social networks: a survey and new perspectives. Social Network Analysis and Mining, 10(1), 1-20.
[14] Chen, X., & Wang, N. (2020). Rumor spreading model considering rumor credibility, correlation and crowd classification based on personality. Scientific reports, 10(1), 1-15.
[15] Li, R., Li, Y., Meng, Z., Song, Y., & Jiang, G. (2020). Rumor Spreading Model Considering Individual Activity and Refutation Mechanism Simultaneously. IEEE Access, 8, 63065-63076.
[16] Yang, S., Jiang, H., Hu, C., Yu, J., & Li, J. (2020). Dynamics of the rumor-spreading model with hesitation mechanism in heterogenous networks and bilingual environment. Advances in Difference Equations, 2020(1), 1-21.
[17] Ai, S., Hong, S., Zheng, X., Wang, Y., & Liu, X. (2021). CSRT rumor spreading model based on complex network. International Journal of Intelligent Systems, 36(5), 1903-1913.
[18] Qiu, L., Jia, W., Niu, W., Zhang, M., & Liu, S. (2020). SIR-IM: SIR rumor spreading model with influence mechanism in social networks. Soft Computing, 1-10.
[19] Zhao, L., Wang, J., Chen, Y., Wang, Q., Cheng, J., & Cui, H. (2012). SIHR rumor spreading model in social networks. Physica A: Statistical Mechanics and its Applications, 391(7), 2444-2453.
[20] Yang, A., Huang, X., Cai, X., Zhu, X., & Lu, L. (2019). ILSR rumor spreading model with degree in complex network. Physica A: Statistical Mechanics and its Applications, 531, 121807.
[21] Tran Son Hai, Le Hoang Thai, Nguyen Thanh Thuy,"Facial Expression Classification Using Artificial Neural Network and K-Nearest Neighbor", International Journal of Information Technology and Computer Science, vol.7, no.3, pp.27-32, 2015.
[22] Saptarsi Goswami, Amlan Chakrabarti,"Feature Selection: A Practitioner View", International Journal of Information Technology and Computer Science, vol.6, no.11, pp.66-77, 2014.