TY - JOUR
T1 - Precautionary rumor containment via trustworthy people in social networks
AU - Fan, Lidan
AU - Wu, Weili
AU - Xing, Kai
AU - Lee, Wonjun
N1 - Publisher Copyright:
© 2016 World Scientific Publishing Company.
PY - 2016/3/1
Y1 - 2016/3/1
N2 - 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.
AB - 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.
KW - Greedy Algorithm
KW - Rumor
KW - social networks
KW - social relation graph
KW - trust
UR - http://www.scopus.com/inward/record.url?scp=85020666269&partnerID=8YFLogxK
U2 - 10.1142/S179383091650004X
DO - 10.1142/S179383091650004X
M3 - Article
AN - SCOPUS:85020666269
SN - 1793-8309
VL - 8
JO - Discrete Mathematics, Algorithms and Applications
JF - Discrete Mathematics, Algorithms and Applications
IS - 1
M1 - 1650004
ER -