Paper Info
Title
Detecting Nasty Comments From Bbs Posts
Abstract
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.
Year
Venue
Keywords
2010
PROCEEDINGS OF THE 24TH PACIFIC ASIA CONFERENCE ON LANGUAGE, INFORMATION AND COMPUTATION
sentence detection, nasty comment, n-gram, SVM, BBS
Field
DocType
Citations 
Information retrieval,Bulletin board system,Computer science,Support vector machine,Artificial intelligence
Conference
0
PageRank 
References 
Authors
0.34
6
2
Name
Order
Citations
PageRank
Tatsuya Ishisaka100.34
Kazuhide Yamamoto220739.66