A Novel Approach To Detect Advertising Spammer In Micro-blog
Recently,with the growth of registered accounts in Micro-blog,the number of abnormal accounts also increased.The emergence of advertising accounts and other unusual account heavily affects the normal order of Micro-blog,therefore,finding out an efficient method to distinguish and classify advertising accounts plays an important role in the Micro-blog ecosystem.Based on the machine learning method,we extract three aspects effective feature sets to design advertising account recognition and classification,and the feature sets contain the following three parts: user profiles,social characteristics and the content of Micro-blog.We crawled 1,000 regular accounts and 1,000 advertising accounts,and handed label them.By using the constructed training set of labeled accounts,the training model of classification model is established.The result demonstrates that the Micro-blog account classification model constructed in this paper can effectively differentiate advertising account and normal account.
Micro-blog Machine Learning Abnormal Accounts Identification Advertising Accounts Classification
Gang Bai Lianzhong Liu Xiongjie Du Yifu Li
School of Computer Science and Engineering Beihang University Beijing,China National Computer Network Emergency Response Technical Team/Coordination Center of China Beijing,Chi
国际会议
重庆
英文
1809-1813
2017-03-25（万方平台首次上网日期，不代表论文的发表时间）