HARK: Harshness-Aware Sentiment Analysis Framework for Product Review (Student Abstract)

Now a day's more and more people are buying products online. In order to enhance customer shopping experience, it has become a common practice for online merchants to enable their customers to write reviews on products that they have purchased. As a result, the number of reviews that a product receives grows rapidly. Manual analysis of customer opinions is very time consuming due to the multitude of contributions. So the sentiment analysis is use to extract, aggregate and analysed the opinions on product from discussion forums. Sentiment analysis has gained much attention in recent years. Sentiment analysis is a kind of text classification that classifies texts based on the sentimental orientation (SO) of opinions they contain. Sentiment analysis of product reviews has recently become very popular in text mining and computational linguistics research. In the field of sentiment analysis there are many algorithms exist to tackle Natural Language Processing problems. Each algorithm is used by several applications. In this paper i have revised the various sentiment analysis based neural network methods. Data used in this study are online product reviews collected from Amazon.com. Experiments for neural network methods which are performed with promising outcomes.