Maximizing social influence on target users

Yu Ting Wen*, Wen-Chih Peng, Hong-Han Shuai

*此作品的通信作者

研究成果: Conference contribution同行評審

9 引文 斯高帕斯(Scopus)

摘要

Influence maximization has attracted a considerable amount of research work due to the explosive growth in online social networks. Existing studies of influence maximization on social networks aim at deriving a set of users (referred to as seed users) in a social network to maximize the expected number of users influenced by those seed users. However, in some scenarios, such as election campaigns and target audience marketing, the requirement of the influence maximization is to influence a set of specific users. This set of users is defined as the target set of users. In this paper, given a target set of users, we study the Target Influence Maximization (TIM) problem with the purpose of maximizing the number of users within the target set. We particularly focus on two important issues: (1) how to capture the social influence among users, and (2) how to develop an efficient scheme that offers wide influence spread on specified subsets. Experiment results on real-world datasets validate the performance of the solution for TIM using our proposed approaches.

原文English
主出版物標題Advances in Knowledge Discovery and Data Mining - 22nd Pacific-Asia Conference, PAKDD 2018, Proceedings
編輯Geoffrey I. Webb, Dinh Phung, Mohadeseh Ganji, Lida Rashidi, Vincent S. Tseng, Bao Ho
發行者Springer Verlag
頁面701-712
頁數12
ISBN(電子)9783319930404
ISBN(列印)9783319930398
DOIs
出版狀態Published - 17 6月 2018
事件22nd Pacific-Asia Conference on Advances in Knowledge Discovery and Data Mining, PAKDD 2018 - Melbourne, Australia
持續時間: 3 6月 20186 6月 2018

出版系列

名字Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
10939 LNAI
ISSN(列印)0302-9743
ISSN(電子)1611-3349

Conference

Conference22nd Pacific-Asia Conference on Advances in Knowledge Discovery and Data Mining, PAKDD 2018
國家/地區Australia
城市Melbourne
期間3/06/186/06/18

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