Role of Machine Learning in Sentiment Analysis- A Review

Amongst the most basic activities in natural language processing is to know and understand low-dimensional vector presentations of words from a huge dataset. The organizational forms embedding system trains word vectors primarily from grammatical rules and semantic relations from the sense, disregarding sentiment polarity in the sentences. While some methods prototype sentiment data from feedback, they ignore specific language in various contexts. If the responded vector is easily adapted to the evaluation of sentiment classification task when the sentimentality keeps changing, the sentiment classification performance will suffer immensely. The methodologies was using to categories sentiment classification are discussed in this paper