计算机工程与应用Issue(5)：116-120,5.DOI:10.3778/j.issn.1002-8331.1311-0204
社交网络节点中心性测度
Centrality for nodes in social networks
摘要
Abstract
In social networks, investigating node influence and influence maximization is an important issue and attracts great interest in the research community. In order to analyze its personal influence and potential influence, it proposes a Personal-Potential Influence(PPI)algorithm, which evaluates the weight of its k-shell, closeness centrality and between-ness centrality by considering the strength of relationship between nodes. The experimental results show that PPI has the higher accuracy in node influence and outperforms other algorithms.关键词
节点影响力/影响力最大化/社交网络/重要节点/中心性Key words
node influence/influence maximization/social network/key node/centrality分类
信息技术与安全科学引用本文复制引用
刘欣,李鹏,刘璟,王娅丹..社交网络节点中心性测度[J].计算机工程与应用,2014,(5):116-120,5.基金项目
湖北省教育厅科研基金资助项目（No.B20101104）；湖北省重点实验室开放基金资助项目（No.znss2013B012）；武汉科技大学科研基金资助项目（No.2009xz1，No.2012xz015）；武汉科技大学大学生科技创新基金研究项目（No.12ZRC061）。 （）
