Influence maximisation in social networks: A target-oriented estimation

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WEB OF SCIENCE

4
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SCOPUS

9

초록

Influence maximisation (IM) is the problem of finding a set of k-seed nodes that could maximize the amount of influence spread in a social network. In this article, we point out that the existing methods are taking the source-oriented estimation (SOE), which is the main reason of their failure in accurately estimating the amount of potential influence spread of an individual node. We propose a novel target-oriented estimation (TOE) that understands information diffusion more accurately as well as remedies the drawback of the existing methods. Our extensive experiments on four real-world datasets demonstrate that our proposed method outperforms the existing methods consistently with respect to the quality of the selected seed set.

키워드

Influence maximisation; information diffusion; social network analysis; COMMUNITY STRUCTURE
제목
Influence maximisation in social networks: A target-oriented estimation
저자
Ko, Yun-Yong; Chae, Dong-Kyu; Kim, Sang-Wook
DOI
10.1177/0165551517748289
발행일
2018-10
유형
Article
저널명
Journal of Information Science
권
44
호
5
페이지
671 ~ 682