摘要
社交网络作为一种新兴的媒体具有广泛的社会影响力,且基于社交网络的营销方式逐渐成为一种新的发展趋势,因此研究社交网络中消息的传播具有重大的现实和经济意义。通过借鉴日常生活中人与人之间的信任原理,提出了一种基于信任度的消息传播模型。该模型首先利用个体的公开信息,使用数据挖掘的算法对个体进行分类;然后,根据同类和不同类个体之间的关系计算个体之间的信任度;最后,使用消息与个体的属性相似性以及信任度来计算消息可能传播范围。给出了相应的计算方法,并与两种基准方法对比,结果表明,该模型在准确度上提升15%左右,而所用时间降低50%以上。与数据集统计结果对比,该实验的结果与统计结果相差5%左右,充分表明该模型在实际应用中有比较好的效果。
As a new media, social network gains a wide range of social influence, and the social network based e- commerce becomes more and more popular, which make the study of information propagation of great significance. A trust based information propagation model was presented in this paper according to the trust relationship between people in daily life. First, the algorithm of data mining was employed on personal information to make the classification of the users. And then the value of trust between the users was calculated according to their relationships. At last, this paper predicted the range of information propagation by using the trust value between the users and messages. Compared with two basic methods, the final experiment shows that the results generated by the model are enhanced by 15% in precision, while the time used decreases more than 50%. The results differ with the statistic results on the dataset at 5%, which shows that the model preforms well in practice.
出处
《计算机应用》
CSCD
北大核心
2014年第2期411-416,共6页
journal of Computer Applications
基金
广东省自然科学基金资助项目(9151009001000043)
关键词
社交网络
数据挖掘
分类算法
信任度
网络的结构聚类算法
消息传播模型
social network
data mining
classification algorithm
trust
Structural Clustering Algorithm for Networks （SCAN）
information propagation model
