Detecting Threats of Violence in Online Discussions Using Bigrams of Important Words

Author(s)

Publication date

2014

Series/Report no

IEEE Joint;

Publisher

IEEE Xplore Digital Library

Document type

Abstract

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.

Keywords

Permanent URL (for citation purposes)

  • http://hdl.handle.net/10642/2368