A study of rumor control strategies on social networks

Tripathy, Rudra M.; Bagchi, Amitabha; Mehta, Sameep

doi:10.1145/1871437.1871737

Cited by 111 publications

(47 citation statements)

References 6 publications

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“…This section revises Tripathy et al's approach [21] for modeling the rumor spreading in Twitter. This model is based on the cascade model [22] and is one of the earliest ABSS rumor spread models proposed for the Twitter case.…”

Section: Baseline Approachmentioning

confidence: 98%

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A Novel Agent-Based Rumor Spreading Model in Twitter

Serrano

Iglesias

Garijo

2015

Proceedings of the 24th International Conference on World Wide Web

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Viral marketing, marketing techniques that use pre-existing social networks, has experienced a significant encouragement in the last years. In this scope, Twitter is the most studied social network in viral marketing and the rumor spread is a widely researched problem. This paper contributes with a (1) novel agent-based social simulation model for rumors spread in Twitter. This model relies on the hypothesis that (2) when a user is recovered, this user will not influence his or her neighbors in the social network to recover. To support this hypothesis: (3) two Twitter rumor datasets are studied; (4) a baseline model which does not include the hypothesis is revised, reproduced, and implemented; (5) and a number of experiments are conducted comparing the real data with the two models results.

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Section: Baseline Approachmentioning

confidence: 98%

“…However, getting an accurate spread model is not the paper goal. Tripathy et al [21] present a study and an evaluation of rumor-like methods for combating the spread of rumors on social networks. They use variants of the independent cascade model [22] for rumor spreading.…”

Section: Related Workmentioning

confidence: 99%

A Novel Agent-Based Rumor Spreading Model in Twitter

Serrano

Iglesias

Garijo

2015

Proceedings of the 24th International Conference on World Wide Web

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“…Finally, in [6] the authors defined a method to infer the topology of networks analyzing the paths used by the nodes of the OSN to spread information. On the other hand, [15] presents and evaluates strategies for controlling the diffusion of rumors within social networks. This is done by injecting in the social network anti-rumors, which are packets of information containing a statement from trusted authority indicating to block the propagation of a particular rumor.…”

Section: Related Workmentioning

confidence: 99%

A rule-based policy language for selective trust propagation in social networks

Braghin

Ferrari

Trombetta

2011

Databases and Social Networks

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Information spreading is a important topic in the area of Online Social Networks (OSNs). Typically, information flows in a careless way among directly connected members of the OSN ("friends"). In this way, it is possible that sensitive information is unintentionally leaked to not entitled or untrusted members. A well-known approach for the management of trust relationships is represented by trust negotiations. In an OSN, trust negotiations can be exploited in a novel way, that is, their outcome can be used to dynamically adjust the trust level between OSN users. Additionally, information about past negotiations between members of the OSN can be propagated in the OSN graph and used by other OSN members to take access control decisions. However, such information can be sensitive and therefore their disclosure should be carefully regulated. To cope with these issues, in this paper we introduce a language for the definition of policies regulating the disclosure of information about past interactions occurred between members of the OSN.

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“…The immunization problem is mathematically equivalent to asking how to disintegrate a given network with a minimum number of node removals, which is very important since in most cases the number of immunization doses is limited or very expensive. Other examples of network disintegration include destabilizing terrorist networks [11] , preventing financial contagion [12] , controlling the rumor diffusion [13] , and perturbing cancer networks [14] . Although the problem of network disintegration is not obtained more attention than the problem of network protection, some related works have been devoted to the study of the attack strategy.…”

Section: Introductionmentioning

confidence: 99%

Key Nodes Mining Algorithm Based on Complex Network

Deng¹,

Wu²,

Yue-jin³

2016

Proceedings of the 2016 International Conference on Computational Science and Engineering (ICCSE 2016)

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Abstract. The problem of network disintegration, such as suppressing the epidemic spreading and destabilizing terrorist networks, has broad applications and recently has attracted more attentions. The fundamental purpose of this study is to find the critical nodes whose deficiency could lead to the network collapse. By now, most related works of attack strategy in complex networks use certain properties of the nodes, while little is known about optimal attack strategy for complex networks. In this paper, we presented an optimized attack strategy model for complex networks and introduced the tabu search into the problem. The network performance is quantitatively measured by natural connectivity, which can be used to effectively characterize the robustness of complex networks. Numerical experiments suggest that our solution can identify the 'best' choice for node failure attack.

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A study of rumor control strategies on social networks

Cited by 111 publications

References 6 publications

A Novel Agent-Based Rumor Spreading Model in Twitter

A Novel Agent-Based Rumor Spreading Model in Twitter

A rule-based policy language for selective trust propagation in social networks

Key Nodes Mining Algorithm Based on Complex Network

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