Automatic verbal aggression detection for Russian and American imageboards
April 22, 2016 ยท Declared Dead ยท ๐ arXiv.org
"No code URL or promise found in abstract"
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Authors
Denis Gordeev
arXiv ID
1604.06648
Category
cs.CL: Computation & Language
Citations
2
Venue
arXiv.org
Last Checked
5 months ago
Abstract
The problem of aggression for Internet communities is rampant. Anonymous forums usually called imageboards are notorious for their aggressive and deviant behaviour even in comparison with other Internet communities. This study is aimed at studying ways of automatic detection of verbal expression of aggression for the most popular American (4chan.org) and Russian (2ch.hk) imageboards. A set of 1,802,789 messages was used for this study. The machine learning algorithm word2vec was applied to detect the state of aggression. A decent result is obtained for English (88%), the results for Russian are yet to be improved.
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