Research Article
Automatic Detection of Hateful Comments in Online Discussion
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@INPROCEEDINGS{10.1007/978-3-319-52569-3_15, author={Hugo Hammer}, title={Automatic Detection of Hateful Comments in Online Discussion}, proceedings={Industrial Networks and Intelligent Systems. Second International Conference, INISCOM 2016, Leicester, UK, October 31 -- November 1, 2016, Revised Selected Papers}, proceedings_a={INISCOM}, year={2017}, month={6}, keywords={Hateful comments Machine learning Threat detection}, doi={10.1007/978-3-319-52569-3_15} }- Hugo Hammer
Year: 2017
Automatic Detection of Hateful Comments in Online Discussion
INISCOM
Springer
DOI: 10.1007/978-3-319-52569-3_15
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.
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