Maximizing the Spread of Effective Information in Social Networks
文献类型：期刊论文
| 作者 | Zhang, Haonan; Fu, Luoyi; Ding, Jiaxin; Tang, Feilong1; Xiao, Yao; Wang, Xinbing; Chen, Guihai; Zhou, Chenghu3 |
| 刊名 | IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING
 |
| 出版日期 | 2023-04-01 |
| 卷号 | 35期号:4页码:4062-4076 |
| 关键词 | Social networking (online) Mouth Smart phones Estimation Approximation algorithms Time complexity Statistics Social network influence maximization information variation greedy algorithm |
| DOI | 10.1109/TKDE.2021.3138783 |
| 文献子类 | Article |
| 英文摘要 | Influence maximization through social networks has aroused tremendous interests nowadays. However, people's various expressions or feelings about a same idea often cause ambiguity via word of mouth. Consequently, the problem of how to maximize the spread of effective information still remains largely open. In this paper, we consider a practical setting where ideas can deviate from their original version to invalid forms during message passing, and make the first attempt to seek a union of users that maximizes the spread of effective influence, which is formulated as an Influence Maximization with Information Variation (IMIV) problem. To this end, we model the information as a vector, and quantify the difference of two arbitrary vectors as a distance by a matching function. We further establish a process where such distance increases with the propagation and ensure the recipient whose vector distance is less than a threshold can be effectively influenced. Due to the NP-hardness of IMIV, we greedily select users that can approximately maximize the estimation of effective propagation. Especially, for networks of small scales, we derive a condition under which all the users can be effectively influenced. Our models and theoretical findings are further consolidated through extensive experiments on real-world datasets. |
| WOS研究方向 | Computer Science ; Engineering |
| WOS记录号 | WOS:000946283700058 |
| 源URL | [http://ir.igsnrr.ac.cn/handle/311030/200711]  |
| 专题 | 资源与环境信息系统国家重点实验室_外文论文 |
| 作者单位 | 1.Shanghai Jiao Tong Univ, Sch Elect Informat & Elect Engn, Shanghai 200240, Peoples R China 2.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, Beijing 100045, Peoples R China 3.Shanghai Jiao Tong Univ, Comp Sci & Engn, Shanghai 200240, Peoples R China |
| 推荐引用方式 GB/T 7714 | Zhang, Haonan,Fu, Luoyi,Ding, Jiaxin,et al. Maximizing the Spread of Effective Information in Social Networks[J]. IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING,2023,35(4):4062-4076. |
| APA | Zhang, Haonan.,Fu, Luoyi.,Ding, Jiaxin.,Tang, Feilong.,Xiao, Yao.,...&Zhou, Chenghu.(2023).Maximizing the Spread of Effective Information in Social Networks.IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING,35(4),4062-4076. |
| MLA | Zhang, Haonan,et al."Maximizing the Spread of Effective Information in Social Networks".IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING 35.4(2023):4062-4076. |
入库方式： OAI收割
来源：地理科学与资源研究所
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