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Automatic Detection of Hateful Comments in Online Discussion

Hammer, Hugo Lewi
Peer reviewed, Journal article
Accepted version
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URI
https://hdl.handle.net/10642/4202
Date
2016
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  • TKD - Institutt for informasjonsteknologi [860]
Original version
Hammer HL: Automatic Detection of Hateful Comments in Online Discussion. In: Maglaras. Industrial Networks and Intelligent Systems, 2016. Springer p. 164-173  
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 learn-

ing. A material of 24,840 sentences from YouTube was manually anno-

tatedasviolentthreatsornot,andwasusedtotrainandtestthemachine

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.
Publisher
Springer

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