Intelligent Sentiment Review Analysis with Short form Words and False Negative Comment Consideration

Data mining is the process of turning raw data into useful information. The main use of data mining is to fetch the required data and extract useful information from the data and to interpret the data. In the existing system, Bag of Words model is used along with Dual sentiment Analysis in order to classify the reviews as positive, negative and neutral. However, the performance of Bag of Words sometimes remains limited due to some fundamental deficiencies in handling the polarity shift problem. The proposed system uses a dictionary based classification for accurately classifying the reviews as positive, negative and neutral. The proposed system additionally analyses the flaws of the existing systems and thereby propose two major features such as identifying the negation oriented sentiments and the conjunction oriented sentiments which require the analysis of pre-conjunction and post conjunction sentences. So the ambiguity is reduced by analyzing such conjunction and negation based sentences. To enhance the accuracy in the classification of neutral reviews, Dual sentiment analysis method is implemented. Both the product owner and the user can identify the quality of the product based on the sentiment graph that is generated based on the reviews for each of the product.