基于分层社区的社交网络异常事件检测模型研究

Research on anomaly Detection Model of Social Network Based on Hierarchical Community

社交网络的数据中蕴含着大量有关现实中各种事件的信息。使用异常事件检测模型准确及时地发现社交网络上传播的异常事件信息,对于实现智慧城市感知社会异常动态事件,有效提高社会管理应对效率具有关键作用。本文定义了基于社交网络的有权无向图,根据异常事件的特征对社交网络中事件进行了主题分类和筛选,构建了一个基于分层社区的异常事件检测模型,从而可以实现对城市区域异常事件的检测。

Social network data contains a lot of information about various events in reality.Using anomaly event detection model to accurately and timely discover the information of abnormal events spread on social networks plays a key role in realizing smart cities’perception of social abnormal dynamic events and effectively improving social management response efficiency.This paper defines a hierarchical community of social network abnormal events Based on the weighted undirected graph,classifies and filters the events in social network according to the characteristics of abnormal events,constructs an abnormal event detection model,and realizes the detection of abnormal events in urban areas.