摘要
近年来微博已经发展为一个影响力巨大的社交网络平台。针对微博的复杂网络特性,提出了对微博用户重要度的算法,从海量微博信息中智能提取重要内容。算法考虑到社交网络的节点间影响以及用户行为的传递性,同时为了提高对海量节点的处理能力,进行了有效的子网分划。通过实验,证明算法能有效分析网络中节点贡献内容的重要度,有助于提高社交网络中舆情监控、分析、管理等工作的效率和准确性。
Recently Weibo becomes a social network platform with huge influence. Based on user importance and user behavior in complex networks, a relationship-based importance algorithm for micro-blog network system is proposed, thus to extract important content from mass information on web. This new approach fully considers the relationships between nodes of social network, and the experiments indicate that this new approach is highly efficient and accurate, and could improve the efficiency of information monitoring and management in micro-blog network.
出处
《信息安全与通信保密》
2013年第1期51-53,共3页
Information Security and Communications Privacy
基金
国家自然科学基金资助项目(批准号:61272441
61171173)
关键词
复杂网络
微博网络
用户行为
重要度分析
complex network
Micro-blog networks
user behavior
importance analysis
