华中科技大学学报（自然科学版）2024，Vol.52Issue(2)：55-61,7.DOI:10.13245/j.hust.240211
基于节点混合阻塞力的影响阻塞最大化算法
Mixed-blocking-ability-based algorithm for influence blocking maximization
摘要
Abstract
To solve the problem of influence blocking maximization in social networks,the concept of mixed blocking force of nodes based on the competitive independent cascade model was introduced,then a greedy heuristic was proposed.With the help of the existing method for calculating the influence probability of nodes,new measures for the blocking ability and diffusion ability of nodes were given,which were used to describe the impact of nodes on the spread of negative information and positive information respectively.Combining with these two capabilities,the mixed blocking force of a node can be calculated.The greedy algorithm selected a node with the largest mixed blocking force as a blocking node during each iteration.Compared with several existing algorithms,it can be seen that these blocking nodes selected by the greedy algorithm have better effective in blocking negative information on classic social network instances.关键词
社交网络/竞争独立级联模型/权重级联模型/影响最大化/影响阻塞最大化Key words
social network/competitive independent cascade model/weight cascade model/influence maximization/influence blocking maximization分类
信息技术与安全科学引用本文复制引用
陈卫东,朱颖慧,钟昊..基于节点混合阻塞力的影响阻塞最大化算法[J].华中科技大学学报（自然科学版）,2024,52(2):55-61,7.基金项目
国家自然科学基金资助项目(61370003). （61370003）
