Precautionary rumor containment via trustworthy people in social networks

被引:5
|
作者
Fan, Lidan [1 ]
Wu, Weili [2 ]
Xing, Kai [2 ]
Lee, Wonjun [3 ]
机构
[1] Univ Kansas, Sch Business, 1450 Jayhawk Blvd, Lawrence, KS 66045 USA
[2] Univ Texas Dallas, Dept Comp Sci, 800 W Campbell Rd, Richardson, TX 75080 USA
[3] Korea Univ, Dept Comp Sci & Engn, 145 Anam Ro, Seoul, South Korea
基金
美国国家科学基金会;
关键词
Rumor; trust; social networks; social relation graph; Greedy Algorithm;
D O I
10.1142/S179383091650004X
中图分类号
O29 [应用数学];
学科分类号
070104 ;
摘要
In a social network, rumor containment is vital, as the diffusion of a rumor will bring terrible results. Precautionary measure can be used to control rumor propagation: Anticipating the spread of a rumor, one can (1) select a set of trustworthy people (TP) in the network, (2) alert the TP about the rumor, and (3) ask the TP to protect their neighbors by sending out alerts. In this paper, we study the problem of how to select the least number of TP, satisfying the requirement that the entire network is protected by the alerts that the TP send. We propose an asymmetric trust (AT) information propagation model. Under this model, we study the Least Number TP Selection (LNTS) problem, establish its NP-hardness and reformulate it as a minimum submodular cover problem. As a result, the Greedy Algorithm is a constant-factor approximation algorithm. Using real-world data, we evaluate the performance of the Greedy Algorithm, and compare it with other algorithms. Experimental results indicate that the Greedy Algorithm performs the best among its competitors.
引用
收藏
页数:18
相关论文
共 50 条
  • [31] Rumor propagation with heterogeneous transmission in social networks
    Vega-Oliveros, Didier A.
    Costa, Luciano da F.
    Rodrigues, Francisco A.
    JOURNAL OF STATISTICAL MECHANICS-THEORY AND EXPERIMENT, 2017,
  • [32] Energy model for rumor propagation on social networks
    Han, Shuo
    Zhuang, Fuzhen
    He, Qing
    Shi, Zhongzhi
    Ao, Xiang
    PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS, 2014, 394 : 99 - 109
  • [33] Detecting rumor outbreaks in online social networks
    Damian Frąszczak
    Social Network Analysis and Mining, 13
  • [34] A review of rumor detection techniques in social networks
    Liu, Yao
    Shen, Hao
    Shi, Lei
    JOURNAL OF INTELLIGENT & FUZZY SYSTEMS, 2023, 44 (03) : 3561 - 3578
  • [35] SIHR rumor spreading model in social networks
    Zhao, Laijun
    Wang, Jiajia
    Chen, Yucheng
    Wang, Qin
    Cheng, Jingjing
    Cui, Hongxin
    PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS, 2012, 391 (07) : 2444 - 2453
  • [36] Dynamics of rumor spreading in mobile social networks
    Wang Hui
    Han Jiang-Hong
    Deng Lin
    Cheng Ke-Qing
    ACTA PHYSICA SINICA, 2013, 62 (11)
  • [37] Rumor correction maximization problem in social networks
    Zhang, Yapu
    Yang, Wenguo
    Du, Ding-Zhu
    THEORETICAL COMPUTER SCIENCE, 2021, 861 : 102 - 116
  • [38] Controlling Rumor Cascade over Social Networks
    Ibrahim, Ragia A.
    Hefny, Hesham A.
    Hassanien, Aboul Ella
    PROCEEDINGS OF THE INTERNATIONAL CONFERENCE ON ADVANCED INTELLIGENT SYSTEMS AND INFORMATICS 2016, 2017, 533 : 456 - 466
  • [39] Rumor Spreading Model Considering Rumor's Attraction in Heterogeneous Social Networks
    Xia, Ling-Ling
    Song, Bo
    Zhang, Liang
    CLOUD COMPUTING AND SECURITY, PT V, 2018, 11067 : 734 - 745
  • [40] Rumor Remove Order Strategy on Social Networks
    Wang, Yuanda
    Wang, Haibo
    Chen, Shigang
    Xia, Ye
    5TH INTERNATIONAL CONFERENCE ON INFORMATION SYSTEM AND DATA MINING (ICISDM 2021), 2021, : 128 - 137