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The paper presents an approach to extraction of current web trends for research into automated recognition of antisocial behaviour in online discussions. Antisocial behaviour is a drawback of online discussions as compared to their advantages such as wisdom of crowds and collective intelligence. The first step to recognition of antisocial behaviour is the identification of web trends connected with it. These are studied in dynamic conditions using sentiment analysis as a webometric. A new sentiment analysis method based on a lexicon was developed. Two modifications of the lexicon sentiment analysis method were designed and tested involving NLP (natural language processing) and an original technique for negations and intensifications processing. The most effective sentiment classification method was used for the extraction of web trends. Extracted web trends were analysed in a dynamic way and findings of this analysis were compared to known historical events.

Sentiment Analysis of Web Trends for the Antisocial Behaviour Detection