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author:

Yang, Dingda (Yang, Dingda.) [1] | Liao, Xiangwen (Liao, Xiangwen.) [2] (Scholars:廖祥文) | Shen, Huawei (Shen, Huawei.) [3] | Cheng, Xueqi (Cheng, Xueqi.) [4] | Chen, Guolong (Chen, Guolong.) [5] (Scholars:陈国龙)

Indexed by:

EI Scopus SCIE

Abstract:

To restrain the spread of harmful information is crucial for the healthy and sustainable development of social networks. We address the problem of restraining the spread of harmful information by immunizing nodes in the networks. Previous works have developed methods based on the network topology or studied how to immunize nodes in the presence of initial infected nodes. These static methods, in which nodes are immunized at once, may have poor performance in the certain situation due to the dynamics of diffusion. To tackle this problem, we introduce a new dynamic immunization problem of immunizing nodes during the process of the diffusion in this paper. We formulate the problem and propose a novel heuristic algorithm by dealing with two sub-problems: (1) how to select a node to achieve the best immunization effect at the present time? (2) whether the selected node should be immunized right now? Finally, we demonstrate the effectiveness of our algorithm through extensive experiments on various real datasets. (C) 2018 Elsevier B.V. All rights reserved.

Keyword:

Dynamic immunization Harmful information diffusion Heuristic algorithm Social network

Community:

  • [ 1 ] [Yang, Dingda]Fuzhou Univ, Coll Phys & Informat Engn, Fuzhou 350116, Fujian, Peoples R China
  • [ 2 ] [Chen, Guolong]Fuzhou Univ, Coll Phys & Informat Engn, Fuzhou 350116, Fujian, Peoples R China
  • [ 3 ] [Liao, Xiangwen]Fuzhou Univ, Coll Math & Comp Sci, Fuzhou 350116, Fujian, Peoples R China
  • [ 4 ] [Shen, Huawei]Chinese Acad Sci, Inst Comp Technol, CAS Key Lab Network Data Sci & Technol, Beijing 100190, Peoples R China
  • [ 5 ] [Cheng, Xueqi]Chinese Acad Sci, Inst Comp Technol, CAS Key Lab Network Data Sci & Technol, Beijing 100190, Peoples R China
  • [ 6 ] [Yang, Dingda]Fuzhou Univ, Fujian Prov Key Lab Network Comp & Intelligent In, Fuzhou 350116, Fujian, Peoples R China
  • [ 7 ] [Liao, Xiangwen]Fuzhou Univ, Fujian Prov Key Lab Network Comp & Intelligent In, Fuzhou 350116, Fujian, Peoples R China
  • [ 8 ] [Chen, Guolong]Fuzhou Univ, Fujian Prov Key Lab Network Comp & Intelligent In, Fuzhou 350116, Fujian, Peoples R China
  • [ 9 ] [Shen, Huawei]Univ Chinese Acad Sci, Beijing 100049, Peoples R China
  • [ 10 ] [Cheng, Xueqi]Univ Chinese Acad Sci, Beijing 100049, Peoples R China

Reprint 's Address:

  • 廖祥文

    [Liao, Xiangwen]Fuzhou Univ, Coll Math & Comp Sci, Fuzhou 350116, Fujian, Peoples R China

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Source :

PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS

ISSN: 0378-4371

Year: 2018

Volume: 503

Page: 640-649

2 . 5

JCR@2018

2 . 8 0 0

JCR@2023

ESI Discipline: PHYSICS;

ESI HC Threshold:158

JCR Journal Grade:2

CAS Journal Grade:3

Cited Count:

WoS CC Cited Count:

SCOPUS Cited Count:

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 0

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