Abstract:

As microblog contains valuable information, data analysis on microblog such as topic detection has become a research hotspot. Due to the high flexibility of microblog′s content and form, noisy data is a big challenge for microblog analysis. Therefore, no effective method has been developed for nonpublic topic Chinese spam microblog filtering until now. To fill this gap, a new method was proposed to fuse multi-angle features extracted from both the content and structure of microblog. The fused features were then employed for filtering spam microblog with classifiers. Experiments on real data demonstrate that the fusion of multi-angle features can effectively improve the performance of spam filtering.

Key words: spam microblog filtering; feature selection; multi-angle features fusion