Negative-Aware Influence Maximization on Social Networks

被引：0
|
作者：
Chen, Yipeng [1 ]
Li, Hongyan [1 ]
Qu, Qiang [1 ,2 ]
机构：
[1] Peking Univ, Sch Elect Engn & Comp Sci, MOE Key Lab Machine Percept, Beijing, Peoples R China
[2] Chinese Acad Sci, Shenzhen Inst Adv Technol, Beijing, Peoples R China
来源：
THIRTY-SECOND AAAI CONFERENCE ON ARTIFICIAL INTELLIGENCE / THIRTIETH INNOVATIVE APPLICATIONS OF ARTIFICIAL INTELLIGENCE CONFERENCE / EIGHTH AAAI SYMPOSIUM ON EDUCATIONAL ADVANCES IN ARTIFICIAL INTELLIGENCE | 2018年
关键词：
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
How to minimize the impact of negative users within the maximal set of influenced users? The Influenced Maximization (IM) is important for various applications. However, few studies consider the negative impact of some of the influenced users. We propose a negative-aware influence maximization problem by considering users' negative impact. A novel algorithm is proposed to solve the problem. Experiments on real-world datasets show the proposed algorithm can achieve 70% improvement on average in expected influence compared with rivals.
引用
收藏
页码：8063 / 8064
页数：2
相关论文
共 50 条
  • [21] Fuzzy sign-aware diffusion models for influence maximization in signed social networks
    Mohammadi, Sohameh
    Nadimi-Shahraki, Mohammad H.
    Beheshti, Zahra
    Zamanifar, Kamran
    [J]. INFORMATION SCIENCES, 2023, 645
  • [22] Social Influence Maximization in Hypergraph in Social Networks
    Zhu, Jianming
    Zhu, Junlei
    Ghosh, Smita
    Wu, Weili
    Yuan, Jing
    [J]. IEEE TRANSACTIONS ON NETWORK SCIENCE AND ENGINEERING, 2019, 6 (04): : 801 - 811
  • [23] Influence Maximization in Signed Networks by Enhancing the Negative Influence
    Dai, Caiyan
    Hu, Kongfa
    [J]. IEEE ACCESS, 2021, 9 : 44084 - 44093
  • [24] Negative-Aware Attention Framework for Image-Text Matching
    Zhang, Kun
    Mao, Zhendong
    Wang, Quan
    Zhang, Yongdong
    [J]. 2022 IEEE/CVF CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION (CVPR 2022), 2022, : 15640 - 15649
  • [25] Influence Maximization in Online Social Networks
    Aslay, Cigdem
    Lakshmanan, Laks V. S.
    Lu, Wei
    Xiao, Xiaokui
    [J]. WSDM'18: PROCEEDINGS OF THE ELEVENTH ACM INTERNATIONAL CONFERENCE ON WEB SEARCH AND DATA MINING, 2018, : 775 - 776
  • [26] Structural Influence Maximization in Social Networks
    Jing, Dong
    Liu, Ting
    [J]. 2019 INTERNATIONAL CONFERENCE ON INTERNET OF THINGS (ITHINGS) AND IEEE GREEN COMPUTING AND COMMUNICATIONS (GREENCOM) AND IEEE CYBER, PHYSICAL AND SOCIAL COMPUTING (CPSCOM) AND IEEE SMART DATA (SMARTDATA), 2019, : 1088 - 1095
  • [27] Fuzzy Influence Maximization in Social Networks
    Zareie, Ahmad
    Sakellariou, Rizos
    [J]. ACM TRANSACTIONS ON THE WEB, 2024, 18 (03)
  • [28] Influence Maximization in Dynamic Social Networks
    Zhuang, Honglei
    Sun, Yihan
    Tang, Jie
    Zhang, Jialin
    Sun, Xiaoming
    [J]. 2013 IEEE 13TH INTERNATIONAL CONFERENCE ON DATA MINING (ICDM), 2013, : 1313 - 1318
  • [29] Influence Maximization in Noncooperative Social Networks
    Yang, Yile
    Li, Victor O. K.
    Xu, Kuang
    [J]. 2012 IEEE GLOBAL COMMUNICATIONS CONFERENCE (GLOBECOM), 2012, : 2834 - 2839
  • [30] Personalized Influence Maximization on Social Networks
    Guo, Jing
    Zhang, Peng
    Zhou, Chuan
    Cao, Yanan
    Guo, Li
    [J]. PROCEEDINGS OF THE 22ND ACM INTERNATIONAL CONFERENCE ON INFORMATION & KNOWLEDGE MANAGEMENT (CIKM'13), 2013, : 199 - 208
12345