摘要
采用超网络方法,基于用户在社交网络上的评分数据,构建模型,以分析在线社交网络的资源评论特点及其演化规律。将用户视为节点,将资源评论关系视为超边,构建了一个节点按泊松过程到达,允许老节点互连的非均齐超网络演化模型。使用泊松过程理论和连续化方法对模型进行分析,获得超度分布的解析表达式,结果表明,该网络具有"富者愈富"现象。并对豆瓣的图书评分数据集进行了数据分析,实证结果与理论分析结果相符合。模型揭示了社交网络中用户个体之间的微观相互作用而导致的资源评论关系的宏观特性和规律。文中提出的方法也可用于分析其他类似的网络。
We employ the hypernetwork method to analyze the user ratings in social networks,in order to describe the characteristics and evolutionary explanation of resources comments in online social networks.We propose a non-uniform hypernetwork evolving model where nodes are reached by the Poisson process and allow the attachment among old nodes.The users are defined as nodes and the resource comments relationship are defined as hyperedges.We analyze the model by using Poisson process theory and a continuity technique,and give a characteristic equation of hyperdegree and obtain the stationary average hyperdegree distribution of the hypernetwork.The analytical result shows that the hypernetwork has a property of ＂the rich get richer＂.An empirical study of Douban books rating dataset supports the theoretical results.The model can reveal the macro characteristics of resource comments relationship,which is caused by the microscopic interactions among individuals.The method proposed is also universal for the analysis of similar networks.
出处
《系统管理学报》
CSSCI
北大核心
2016年第5期852-857,867,共7页
Journal of Systems & Management
基金
国家自然科学基金资助项目(71571119)
教育部人文社会科学研究项目(16YJC870012)
国家统计局重点项目(2015LZ49)
青岛市社会科学规划项目(QDSKL150462)
关键词
社交网络
超图
超网络
资源评论关系
social network
hypergraph
hypernetwork
resource comments relationship
