摘要
意见领袖发现在舆情监测、市场推广、信息传播等领域具有重要的理论指导意义和实际应用价值。针对传统意见领袖挖掘算法片面考虑目标单一属性、缺乏话题相关性、评估缺乏客观性等问题,提出了一种基于改进拓扑势的意见领袖挖掘ITP算法。该算法结合具体节点的客观属性和网络结构,采用数据偏差对主观权重进行修正,可客观地对目标节点进行评估,挖掘意见领袖。对真实微博数据集进行实验,结果表明与传统的3种方法相比,所提出的算法能挖掘不同背景下的意见领袖,具有较高的相关性和准确度。
Opinion leaders mining has important theoretical guiding significance as well as practical application value in many fields such as public opinion monitoring, market promotion and information transmission. As traditional opinion leader mining algorithms have the shortcomings of one-sidedly considering the target property, subjective assessments and lacking of relevance, this paper proposed an improved topology-potential-based opinion leader mining algorithm. Combining with objective attributes and the network structure of specific nodes, this algorithm uses data deviation to correct subjective weight, and evaluates the target node objectively, thereby mining opinion leaders. According to the realistic Microblog statistics, the algorithm proposed in this paper is superior to traditional algorithms in accuracy and relevance,and can mine opinion leaders from different backgrounds.
出处
《计算机科学》
CSCD
北大核心
2016年第6期194-198,共5页
Computer Science
基金
国家自然科学基金-民航联合基金(U1433116)
航空科学基金(20145752033)资助
关键词
社会网络
意见领袖
权重修正
拓扑势
Social network, Opinion leader, Weight correction, Topology potential