IMVis: Visual analytics for influence maximization algorithm evaluation in hypergraphs

作     者：Jin Xu Chaojian Zhang Ming Xie Xiuxiu Zhan Luwang Yan Yubo Tao Zhigeng Pan 

作者机构：Hangzhou Normal UniversityHangzhouChina Zhejiang UniversityHangzhouChina Nanjing University of Information Science and TechnologyNanjingChina 

出 版 物：《Visual Informatics》 (可视信息学（英文）)

年 卷 期：2024年第8卷第2期

页      面：13-26页

核心收录：

学科分类：07[理学] 0701[理学-数学] 070101[理学-基础数学] 

基　　金：Zhejiang Provincial Natural Science Foundation of China(LQ22F020017) National Natural Science Foundation of China(62302137) Open Project Program of the State Key Lab of CAD&CG of Zhejiang University(A2104) 

主　　题：Influence maximization evaluation Comparative visual analysis Visual analytics 

摘      要：Influence maximization(IM)algorithms play a significant role in hypergraph analysis tasks,such as epidemic control analysis,viral marketing,and social influence analysis,and various IM algorithms have been *** main challenge lies in IM algorithm evaluation,due to the complexity and diversity of the spreading processes of different IM algorithms in different *** evaluation methods mainly leverage statistical metrics,such as influence spread,to quantify overall performance,but do not fully unravel spreading characteristics and *** this paper,we propose an exploratory visual analytics system,IMVis,to assist users in exploring and evaluating IM algorithms at the overview,pattern,and node levels.A spreading pattern mining method is first proposed to characterize spreading processes and extract important spreading patterns to facilitate efficient analysis and comparison of IM *** visualization glyphs are designed to comprehensively reveal both temporal and structural features of IM algorithms’spreading processes in hypergraphs at multiple *** effectiveness and usefulness of IMVis are demonstrated through two case studies and expert interviews.