Automatic Detection of Hateful Comments in Online Discussion

被引:17
作者
Hammer, Hugo Lewi [1 ]
机构
[1] Oslo & Akershus Univ, Coll Appl Sci, Oslo, Norway
来源
INDUSTRIAL NETWORKS AND INTELLIGENT SYSTEMS, INISCOM 2016 | 2017年 / 188卷
关键词
Hateful comments; Machine learning; Threat detection;
D O I
10.1007/978-3-319-52569-3_15
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Making violent threats towards minorities like immigrants or homosexuals is increasingly common on the Internet. We present a method to automatically detect threats of violence using machine learning. A material of 24,840 sentences from YouTube was manually annotated as violent threats or not, and was used to train and test the machine learning model. Detecting threats of violence works quit well with an error of classifying a violent sentence as not violent of about 10% when the error of classifying a non-violent sentence as violent is adjusted to 5%. The best classification performance is achieved by including features that combine specially chosen important words and the distance between those in the sentence.
引用
收藏
页码:164 / 173
页数:10
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