Controlling Spread of Rumor Using Neighbor Centrality

Mehta, Abhinav; Mukhoty, B.; Gupta, Ruchir

doi:10.5506/aphyspolb.47.2325

Cited by 5 publications

(2 citation statements)

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“…In fact, when seeking exact solutions to describe charged compact spheres, many researchers have electrified the well known uncharged solutions found in the past. For example, Kuchowicz [14] solutions have been charged by Nduka [15] and Adler [16]; Wyman [17] solutions by Singh and Yadav [18], Nduka [19] and Klein [20]; Schwarzschild's solution by Gupta Kumar [21], Guilfoyle [22], Gupta et al [23], Florides [24] and Banerjee and Som [25]; Tolman [26] solutions by Cataldo and Mitskievic [27], Tikekar [28] and Pant and Sah [29]; Durga-pal and Fuloria [30] superdense star by Gupta and Maurya [31]; and Finch and Skea [32] neutron star model by Hansraj and Maharaj [33]. In this scenario the charged models of Thirukkanesh and Maharaj [34,35], Maharaj and Thirukkanesh [36], Maurya et al [37], Maurya and Gupta [38][39][40][41] and Gupta and Kumar [42] are notable.…”

Section: Introductionmentioning

confidence: 99%

Charged analogue of well behaved neutral spheres: an algorithmic approach

Thirukkanesh¹,

Ragel

2016

Chinese Phys. C

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We establish a systematic algorithmic approach that generates new classes of solutions to the Einstein-Maxwell system in static spherically symmetric spacetime from well known uncharged solutions. A particular case is shown to satisfy all major physical features of a realistic charged star including the standard point-wise energy conditions of normal matter. The solution matches smoothly with the exterior Reissner-Nordström metric at the pressure free interface. The study, which is reported for a particular choice of gravitational potential, encourages similar approaches to study electrification of well known physically realistic uncharged models.

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Section: Introductionmentioning

confidence: 99%

Charged analogue of well behaved neutral spheres: an algorithmic approach

Thirukkanesh¹,

Ragel

2016

Chinese Phys. C

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“…[17] Mehta et al considered the effect of node importance on suppressing the spread of public opinion and proposed a new measure of node importance, finding that the spread of information could be effectively reduced by suppressing important nodes. [18] Guo et al established a public-opinion communication model based on irrational game theory. Simulation analysis showed that increasing social deterrence, controlling the spread of opinion leaders, and providing positive news could suppress the spread of rumors.…”

Section: Introductionmentioning

confidence: 99%

Direct immune-SCIR public-opinion propagation model based on real-time online users*

Wang¹,

Guo²,

Li³

et al. 2020

Chinese Phys. B

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Current public-opinion propagation research usually focused on closed network topologies without considering the fluctuation of the number of network users or the impact of social factors on propagation. Thus, it remains difficult to accurately describe the public-opinion propagation rules of social networks. In order to study the rules of public opinion spread on dynamic social networks, by analyzing the activity of social-network users and the regulatory role of relevant departments in the spread of public opinion, concepts of additional user and offline rates are introduced, and the direct immune-susceptible, contacted, infected, and refractory (DI-SCIR) public-opinion propagation model based on real-time online users is established. The interventional force of relevant departments, credibility of real information, and time of intervention are considered, and a public-opinion propagation control strategy based on direct immunity is proposed. The equilibrium point and the basic reproduction number of the model are theoretically analyzed to obtain boundary conditions for public-opinion propagation. Simulation results show that the new model can accurately reflect the propagation rules of public opinion. When the basic reproduction number is less than 1, public opinion will eventually disappear in the network. Social factors can significantly influence the time and scope of public opinion spread on social networks. By controlling social factors, relevant departments can analyze the rules of public opinion spread on social networks to suppress the propagate of negative public opinion and provide a powerful tool to ensure security and stability of society.

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