A rumor spreading model with variable forgetting rate

Zhao, Laijun; Xie, Weihao; Gao, Hui; Qiu, Xiaoyan; Wang, Xiaoli; Zhang, Shuhai

doi:10.1016/j.physa.2013.07.080

Cited by 97 publications

(53 citation statements)

References 22 publications

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“…The process of SIAR rumor-spreading is shown in Figure 1. The third rule conforms to the hypothesis [1,[13][14][15][16][17][18][19][20][21] that an active spreader (i.e., infected individual) stops spreading the rumor because he learns that it has lost its "news value"; if this happens as soon as he meets another individual (that is, spreader or stifler or authoritative individual) knowing or refuting the rumor, then transitions from infected state (I) to removed state (R) occur as a result of II, IA, and IR encounters. The above assumptions are derived from the rumor diffusion mechanism of online social network and different people's attitudes to rumors.…”

Section: Siar Rumor-spreading Modelsupporting

confidence: 69%

“…In the previous SIR models [13][14][15][16][17] of rumor spreading based on complex networks, individuals are always divided into three categories which are ignorants (S), spreaders (I), and stiflers (R). Compared with the previous SIR models, in this paper we introduce a new authoritative (A) state into the SIAR model, which is defined in the following way: S, I, A, R stand for the people who never heard rumor (susceptible, similar to ignorants), the people who spread the rumor (infected, similar to spreaders), the people who spread the authoritative information (authoritative), and the people who heard the rumor but had no interest in spreading it (removed, similar to stiflers), respectively.…”

Section: Siar Rumor-spreading Modelmentioning

confidence: 99%

“…Thus, rumors and authoritative information spread in the same network. However, the above studies [10][11][12] did not provide a realistic description of this situation, and many other works [13][14][15][16][17][18][19][20][21] are mainly involved the diffusion of a single rumor. In order to provide a relatively realistic description of the interaction between rumors and authoritative information, we introduce a new SIAR model of rumor-spreading on complex networks considering the hysteresis phenomenon of authoritative information which lags behind the rumor.…”

Section: Introductionmentioning

confidence: 97%

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Modeling and Analyzing the Interaction between Network Rumors and Authoritative Information

Xia

Jiang

Song

et al. 2015

Entropy

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Abstract:In this paper, we propose a novel two-stage rumor spreading SusceptibleInfected-Authoritative-Removed (SIAR) model for complex homogeneous and heterogeneous networks. The interaction Markov chains (IMC) mean-field equations based on the SIAR model are derived to describe the dynamic interaction between the rumors and authoritative information. We use a Monte Carlo simulation method to characterize the dynamics of the Susceptible-Infected-Removed (SIR) and SIAR models, showing that the SIAR model with consideration of authoritative information gives a more realistic description of propagation features of rumors than the SIR model. The simulation results demonstrate that the critical threshold λc of the SIAR model has the tiniest increase than the threshold of SIR model. The sooner the authoritative information is introduced, the less negative impact the rumors will bring. We also get the result that heterogeneous networks are more prone to the spreading of rumors. Additionally, the inhibition of rumor spreading, as one of the characteristics of the new SIAR model itself, is instructive for later studies on the rumor spreading models and the controlling strategies.

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Section: Siar Rumor-spreading Modelsupporting

confidence: 69%

Section: Siar Rumor-spreading Modelmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 97%

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Modeling and Analyzing the Interaction between Network Rumors and Authoritative Information

Xia

Jiang

Song

et al. 2015

Entropy

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“…Rumor spreading is a fundamental problem and has been widely studied by scholars [1][2][3][4][5][6][7][8]. Rumor is often defined as the spreading of public interested things, events or unconfirmed interpretations of problems through various channels.…”

Section: Introductionmentioning

confidence: 99%

Rumor spreading model considering hesitating mechanism in complex social networks

Xia

Jiang

Song

et al. 2015

Physica A: Statistical Mechanics and its Applications

204

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“…Their research in Ref. [7] showed that when the forgetting rate is a variable, the final size of the rumor is much larger than the forgetting rate is assumed as a constant. Though rumors and epidemics are considered as similar, there are quite lots of differences between the mathematical models for them.…”

Section: Introductionmentioning

confidence: 99%

Research on rumor early warning mechanism based on kinetic energy

Li¹,

Fengming²

2016

Proceedings of the 2015 4th National Conference on Electrical, Electronics and Computer Engineering

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Abstract. Network rumors have become a severe scourge disturbing people's network life, even endangering social stability and national security. The best way to control rumor propagation is to discover earlier, so as to take actions to govern rumor before it breaks out. In this paper, from the aspects of rumor itself and rumor's audiences, taking rumor's importance and the number of spreaders as well as social environment into consideration, we propose a early warning model of network rumors based on kinetic energy. The kinetic energy is used to measure a message's attraction. When the attraction is beyond the threshold, some measures should be taken to monitor this message. If this message is judged as a rumor, the government should control the message at once and publish official information at the same time. Several experiments were conducted to verify the model's accuracy and effectiveness.

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A rumor spreading model with variable forgetting rate

Cited by 97 publications

References 22 publications

Modeling and Analyzing the Interaction between Network Rumors and Authoritative Information

Modeling and Analyzing the Interaction between Network Rumors and Authoritative Information

Rumor spreading model considering hesitating mechanism in complex social networks

Research on rumor early warning mechanism based on kinetic energy

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