Automatic Detection of Verbal Aggression for Russian and American Imageboards

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 learning ways of automatic detection of verbal aggression for the most popular American (4chan.org) and Russian (2ch.hk) imageboards. The study material consists of 1,802,789 messages. 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.