Influence analysis in social networks: A survey

被引:175
|
作者
Peng, Sancheng [1 ,2 ]
Zhou, Yongmei [1 ,2 ]
Cao, Lihong [3 ]
Yu, Shui [4 ]
Niu, Jianwei [5 ]
Jia, Weijia [6 ]
机构
[1] Guangdong Univ Foreign Studies, Sch Informat Sci & Technol, Guangzhou 510420, Guangdong, Peoples R China
[2] Guangdong Univ Foreign Studies, Lab Language Engn & Comp, Guangzhou 510420, Guangdong, Peoples R China
[3] Guangdong Univ Foreign Stidies, Sch English & Educ, Guangzhou 510420, Guangdong, Peoples R China
[4] Deakin Univ, Sch Informat Technol, 221 Burwood HWY, Burwood, Vic 3125, Australia
[5] Beihang Univ, State Key Lab Virtual Real Technol & Syst, Beijing 100191, Peoples R China
[6] Shanghai Jiao Tong Univ, Dept Comp Sci & Engn, Shanghai 200240, Peoples R China
基金
中国国家自然科学基金;
关键词
Social networks; Influence analysis; Social influence; Evaluation metric; Influence maximization; INFLUENCE MAXIMIZATION; CENTRALITY; PROPAGATION;
D O I
10.1016/j.jnca.2018.01.005
中图分类号
TP3 [计算技术、计算机技术];
学科分类号
0812 ;
摘要
Complementary to the fancy applications of social networks, influence analysis is an indispensable technique supporting these practical applications. In recent years, this emerging research branch has obtained significant attention from both industry and academia. In this new territory, researchers are facing many unprecedented theoretical and practical challenges. Thus, in this survey, we aim to pave a comprehensive and solid starting ground for interested readers by soliciting the latest work in this area. Firstly, we provide an overview of social networks, including definition, and types of social networks. Secondly, we present the current understanding of social influence analysis from different levels, such as its definition, properties, architecture, applications, and diffusion models. Thirdly, we discuss the evaluation metrics for social influence. Fourthly, we summarize the existing evaluation models on social influence in social networks. We further provide an overview of the existing methods for influence maximization. Finally, we discuss the problems of current algorithms and future trends from various perspectives in this field. We hope this work will shed light for more and more forthcoming researchers to further explore the uncharted part of this promising research field.
引用
收藏
页码:17 / 32
页数:16
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