Positive influence maximization and negative influence minimization in signed networks under competitive independent cascade model

Cheng En Sung, Hao Shang Ma, Jen Wei Huang

研究成果: Conference contribution

1 引文 斯高帕斯(Scopus)

摘要

Influence maximization refers to the process of identifying a predefined number of nodes within a given social network with the aim of maximizing the spread of influence. Most previous work has focused on unsigned networks, which means the existence of polarity relationships has largely been disregarded. In this work, we define a Sign-aware Influence Maximization (SIM) problem, which involves identification of the seed set that would simultaneously maximize positive influence and minimize negative influence. We begin by considered competitive influence under various dominance mechanisms on SCIC model, which extends the classic Independent Cascade (IC) model by incorporating binary opinions and signed relationships. We then proved that the influence of SIM under the SCIC model is non-monotonic and non-submodular, which implies that simple greedy hill-climbing would be unable to achieve an approximation ratio of 1-1/e in seeking to resolve the SIM problem. We then developed a simulation-based algorithm called Sign-aware Competitive Maximum Influence Arborescence (S-CMIA) to simulate the propagation of influence within a local region. Experiment results demonstrate the superiority of the proposed algorithm over existing methods in resolving the SIM problem in terms of reward.

原文English
主出版物標題Proceedings - 2020 IEEE 7th International Conference on Data Science and Advanced Analytics, DSAA 2020
編輯Geoff Webb, Zhongfei Zhang, Vincent S. Tseng, Graham Williams, Michalis Vlachos, Longbing Cao
發行者Institute of Electrical and Electronics Engineers Inc.
頁面236-244
頁數9
ISBN(電子)9781728182063
DOIs
出版狀態Published - 2020 十月
事件7th IEEE International Conference on Data Science and Advanced Analytics, DSAA 2020 - Virtual, Sydney, Australia
持續時間: 2020 十月 62020 十月 9

出版系列

名字Proceedings - 2020 IEEE 7th International Conference on Data Science and Advanced Analytics, DSAA 2020

Conference

Conference7th IEEE International Conference on Data Science and Advanced Analytics, DSAA 2020
國家/地區Australia
城市Virtual, Sydney
期間20-10-0620-10-09

All Science Journal Classification (ASJC) codes

  • 電腦視覺和模式識別
  • 決策科學(雜項)
  • 統計、概率和不確定性
  • 分析
  • 離散數學和組合

指紋

深入研究「Positive influence maximization and negative influence minimization in signed networks under competitive independent cascade model」主題。共同形成了獨特的指紋。

引用此