dc.contributor.author | Hammer, Hugo Lewi | |
dc.date.accessioned | 2017-01-25T10:03:04Z | |
dc.date.accessioned | 2017-03-10T10:14:25Z | |
dc.date.available | 2017-01-25T10:03:04Z | |
dc.date.available | 2017-03-10T10:14:25Z | |
dc.date.issued | 2016 | |
dc.identifier.citation | Hammer HL: Automatic Detection of Hateful Comments in Online Discussion. In: Maglaras. Industrial Networks and Intelligent Systems, 2016. Springer p. 164-173 | language |
dc.identifier.issn | 1867-8211 | |
dc.identifier.issn | 1867-822X | |
dc.identifier.uri | https://hdl.handle.net/10642/4202 | |
dc.description.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. | language |
dc.language.iso | en | language |
dc.publisher | Springer | language |
dc.rights | Original available at www.springerlink.com | language |
dc.subject | Hateful comments | language |
dc.subject | Machine learning | language |
dc.subject | Threat detection | language |
dc.title | Automatic Detection of Hateful Comments in Online Discussion | language |
dc.type | Peer reviewed | |
dc.type | Journal article | |
dc.date.updated | 2017-01-25T10:03:04Z | |
dc.description.version | acceptedVersion | language |
dc.identifier.cristin | 1437259 | |
dc.source.isbn | 978-3-319-52568-6 | |