微博中个人与非个人用户分类方法研究  

Human and Nonhuman User Classification in Micro-blog

作　　者：薛云霞[1] 李寿山[1] 阮进[2] 

机构地区：[1]苏州大学自然语言处理实验室,苏州215006 [2]海军驻河海大学选培办,南京210000

出　　处：《山西大学学报（自然科学版）》2015年第2期192-198,共7页Journal of Shanxi University(Natural Science Edition)

基　　金：国家自然科学基金(61375073)

摘　　要：分别利用用户名和微博文本对个人与非个人两种用户类型进行判别,并对不同的特征(例如:字特征、词特征等)进行研究分析;其次,在针对用户名和微博文本的两个分类器的基础上,使用贝叶斯融合方法进行分类器融合,充分利用两种文本分类信息同时进行用户类型判断。实验结果表明此方法可以达到较高的识别准确率,并且分类器融合方法明显优于仅利用用户名或者微博文本的分类方法。We focus on classifying the users into human or nonhuman ones,i.e.recognizing the human or nonhuman（e.g.,organization）users with the information provided by the Micro-blog.First,we propose a classification method using either user names or messages（sent by the users）to recognize human or nonhuman user.The different types of features（e.g.,character and word features）are investigated to perform the classification.Second,on the basis of the two classifiers trained with user names and messages,we employ Bayes rule to combine the two classifiers so as to make the prediction with classification knowledge from both the user names and messages.The experimental results demonstrate the effectiveness of this approach,and the combination method outperforms the individual classifier trained with only user names or messages.

关 键 词：个人用户识别 新浪微博 文本分类 自然语言处理 社交网络 

分 类 号：TP391.1[自动化与计算机技术—计算机应用技术]