Modeling rumor propagation and refutation with time effect in online social networks

Rumor propagation and refutation form an important issue for spreading dynamics in online social networks (OSNs). In this paper, we introduce a novel two-stage rumor propagation and refutation model with time effect for OSNs. The dynamical mechanism of rumor propagation and refutation with time effect is investigated deeply. Then a two-stage model and the corresponding mean-field equations in both homogeneous and heterogeneous networks are obtained. Monte Carlo simulations are conducted to characterize the dynamics of rumor propagation and refutation in both Watts–Strogatz network and Barabasi–Albert network. The results show that heterogeneous networks yield the most effective rumor and anti-rumor spreading. Besides, the sooner authority releases anti-rumor and the more attractive anti-rumor is, the less rumor influence is. What’s more, these findings suggest that individuals’ ability to control themselves and identify rumor accurately should be improved to reduce negative impact of rumor effectively. The results are helpful to understand better the mechanism of rumor propagation and refutation in OSNs.

[1]  Hao Wang,et al.  Measuring robustness of community structure in complex networks , 2014, ArXiv.

[2]  Mylène C. Q. Farias,et al.  Detecting tampering in audio-visual content using QIM watermarking , 2016, Inf. Sci..

[3]  D. Zanette.  Dynamics of rumor propagation on small-world networks. , 2001, Physical review. E, Statistical, nonlinear, and soft matter physics.

[4]  Yamir Moreno,et al.  Theory of Rumour Spreading in Complex Social Networks , 2007, ArXiv.

[5]  Liang Zhao,et al.  Time series clustering via community detection in networks , 2015, Inf. Sci..

[6]  Gang Xiang,et al.  Anti-rumor dynamics and emergence of the timing threshold on complex network , 2013, 1310.7198.

[7]  Yicheng Zhang,et al.  Dynamics of information diffusion and its applications on complex networks , 2016 .

[8]  Bo Song,et al.  Rumor spreading model considering hesitating mechanism in complex social networks , 2015 .

[9]  Bo Song,et al.  Modeling and Analyzing the Interaction between Network Rumors and Authoritative Information , 2015, Entropy.

[10]  Aihua Li,et al.  Fast and Accurate Mining the Community Structure: Integrating Center Locating and Membership Optimization , 2016, IEEE Transactions on Knowledge and Data Engineering.

[11]  Soodeh Hosseini,et al.  A model for malware propagation in scale-free networks based on rumor spreading process , 2016, Comput. Networks.

[12]  Haiyan Wang,et al.  Complex dynamic behavior of a rumor propagation model with spatial-temporal diffusion terms , 2016, Inf. Sci..

[13]  Hong Huang,et al.  Risk analysis for rumor propagation in metropolises based on improved 8-state ICSAR model and dynamic personal activity trajectories , 2016 .

[14]  Shouming Zhong,et al.  Web malware spread modelling and optimal control strategies , 2017, Scientific Reports.

[15]  Yun Xie,et al.  Affinity based information diffusion model in social networks , 2014 .

[16]  Bo Zhang,et al.  Dynamic 8-state ICSAR rumor propagation model considering official rumor refutation , 2014 .

[17]  Yaming Zhang,et al.  Rumor and authoritative information propagation model considering super spreading in complex social networks , 2018, Physica A: Statistical Mechanics and its Applications.

[18]  Yiliang Han,et al.  Rumor Spreading Model with Trust Mechanism in Complex Social Networks , 2013 .

[19]  Shuai Zhang,et al.  Improved efficient static weighted routing strategy on two-layer complex networks , 2015 .

[20]  Chao Liu,et al.  Modeling the spread of malware with the influence of heterogeneous immunization , 2016 .

[21]  Chuang Liu,et al.  How events determine spreading patterns: information transmission via internal and external influences on social networks , 2015, ArXiv.

[22]  Bo Han,et al.  Lossless Compression of Data Tables in Mobile Devices by Using Co-clustering , 2016, Int. J. Comput. Commun. Control.

[23]  Xi Xiong,et al.  Influence analysis of information erupted on social networks based on SIR model , 2015 .

[24]  Yamir Moreno,et al.  Dynamics of rumor spreading in complex networks. , 2003, Physical review. E, Statistical, nonlinear, and soft matter physics.

[25]  Jie Cao,et al.  Game theory based emotional evolution analysis for chinese online reviews , 2016, Knowl. Based Syst..

[26]  Ping Li,et al.  SICR rumor spreading model in complex networks: Counterattack and self-resistance , 2014 .

[27]  Komi Afassinou.  Analysis of the impact of education rate on the rumor spreading mechanism , 2014 .

[28]  Hui-Jia Li,et al.  Social significance of community structure: Statistical view , 2015, Physical review. E, Statistical, nonlinear, and soft matter physics.

[29]  Dong Liu,et al.  Semi-supervised community detection using label propagation , 2014 .

[30]  Yihao Zhang,et al.  Modeling the propagation of mobile malware on complex networks , 2016, Commun. Nonlinear Sci. Numer. Simul..

[31]  Jinghua Xiao,et al.  Impact of the time pattern of human behaviors on information spreading , 2014 .

[32]  Yi Zhang,et al.  Event ambiguity fuels the effective spread of rumors , 2015 .

[33]  Xiang Ao,et al.  Energy model for rumor propagation on social networks , 2014 .

[34]  Shunjiang Ni,et al.  Dynamics of public opinion under the influence of epidemic spreading , 2016 .

[35]  Chuang Liu,et al.  Emergence of Blind Areas in Information Spreading , 2013, PloS one.

[36]  Guanrong Chen,et al.  Spreading dynamics and global stability of a generalized epidemic model on complex heterogeneous networks , 2012 .

[37]  Yaohui Pan,et al.  Identifying the direct risk source to contain epidemics more effectively. , 2016, Physical review. E.

[38]  Yun Liu,et al.  SHIR competitive information diffusion model for online social media , 2016 .

[39]  Jing Wang,et al.  SIR rumor spreading model considering the effect of difference in nodes’ identification capabilities , 2017 .

[40]  Ping Jiang,et al.  Stability analysis and control models for rumor spreading in online social networks , 2017 .

[41]  Wei Huang,et al.  Rumor spreading model with consideration of forgetting mechanism: A case of online blogging LiveJournal , 2011 .

[42]  Chuang Liu,et al.  Information spreading on dynamic social networks , 2012, Commun. Nonlinear Sci. Numer. Simul..

[43]  Duncan J. Watts,et al.  Collective dynamics of ‘small-world’ networks , 1998, Nature.

[44]  Albert,et al.  Emergence of scaling in random networks , 1999, Science.