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Hu, YQ; Ji, SG; Jin, YL; Feng, L3,4; Stanley, HE; Havlin, S7
Local structure can identify and quantify influential global spreaders in large scale social networks
发表期刊PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA
语种英语
关键词COMPLEX NETWORKS EPIDEMICS VIRUSES
摘要Measuring and optimizing the influence of nodes in big-data online social networks are important for many practical applications, such as the viral marketing and the adoption of new products. As the viral spreading on a social network is a global process, it is commonly believed that measuring the influence of nodes inevitably requires the knowledge of the entire network. Using percolation theory, we show that the spreading process displays a nucleation behavior: Once a piece of information spreads from the seeds to more than a small characteristic number of nodes, it reaches a point of no return and will quickly reach the percolation cluster, regardless of the entire network structure; otherwise the spreading will be contained locally. Thus, we find that, without the knowledge of the entire network, any node's global influence can be accurately measured using this characteristic number, which is independent of the network size. This motivates an efficient algorithm with constant time complexity on the long-standing problem of best seed spreaders selection, with performance remarkably close to the true optimum.
2018
ISSN0027-8424
卷号115期号:29页码:7468-7472
学科领域Science & Technology - Other Topics
学科门类Multidisciplinary Sciences
DOI10.1073/pnas.1710547115
收录类别SCIE
引用统计
文献类型期刊论文
条目标识符http://ir.itp.ac.cn/handle/311006/22861
专题理论物理所科研产出_SCI论文
作者单位1.Sun Yat Sen Univ, Sch Data & Comp Sci, Guangzhou 510006, Guangdong, Peoples R China
2.Southwest Jiaotong Univ, Sch Informat Sci & Technol, Chengdu 610031, Sichuan, Peoples R China
3.Chinese Acad Sci, Inst Theoret Phys, Key Lab Theoret Phys, Beijing 100190, Peoples R China
4.Agcy Sci Technol & Res, Comp Sci, Inst High Performance Comp, Singapore 138632, Singapore
5.Natl Univ Singapore, Dept Phys, Singapore 117551, Singapore
6.Boston Univ, Ctr Polymer Studies, Boston, MA 02215 USA
7.Boston Univ, Dept Phys, 590 Commonwealth Ave, Boston, MA 02215 USA
8.Bar Ilan Univ, Dept Phys, IL-52900 Ramat Gan, Israel
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Hu, YQ,Ji, SG,Jin, YL,et al. Local structure can identify and quantify influential global spreaders in large scale social networks[J]. PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA,2018,115(29):7468-7472.
APA Hu, YQ,Ji, SG,Jin, YL,Feng, L,Stanley, HE,&Havlin, S.(2018).Local structure can identify and quantify influential global spreaders in large scale social networks.PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA,115(29),7468-7472.
MLA Hu, YQ,et al."Local structure can identify and quantify influential global spreaders in large scale social networks".PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA 115.29(2018):7468-7472.
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