Detecting Nasty Comments from BBS Posts
Tatsuya Ishisaka, Kazuhide Yamamoto · Institutional Repositories DataBase (IRDB) · 2010
We propose a method to detect Japanese nasty comments from posts on bulletin board systems (BBS). Nasty comments can cause many social problem, because they express potentially harmful words and phrases. There are methods to recognize harmful words, but they are insufficient. Therefore, we present a method for detecting such comments on a BBS with many posts using an n-gram model. In addition, we compared our method with a support vector machine (SVM) that is based on nasty words. As a result, we detected nasty comments that are different to those by the SVM. We also observe higher detection accuracy by combining two methods.