Sentiment analysis or opinion mining is one of the fastest growing fields with its demand and potential benefits that is increasing every day. With the onset of the internet and modern technology, there has been a vigorous growth in the amount of data. Each individual is able to express his/her own ideas freely on social media. All of this data can be analysed and used in order to draw benefits and quality information. In this paper, the focus is on cyber-hate classification based on for public opinion or views, since the spread of hate speech using social media can have disruptive impacts on social sentiment analysis. In particular, here proposing a modified fuzzy approach with two stage training for dealing with text ambiguity and classifying three type approach positive, negative and neutral sentiment, and compare its performance with those popular methods as well as some existing fuzzy approaches.

Ambiguity, cyber hate, fuzzy, Sentiment analysis

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