Soft Computing, Artificial Intelligence and Applications

Deep Learning Sentiment Analysis of Amazon.Com Reviews and Ratings Nishit Shrestha and Fatma Nasoz University of Nevada Las Vegas, USA ABSTRACT Our study employs sentiment analysis to evaluate the compatibility of Amazon.com reviews with their corresponding ratings. Sentiment analysis is the task of identifying and classifying the sentiment expressed in a piece of text as being positive or negative. On e-commerce websites such as Amazon.com, consumers can submit their reviews along with a specific polarity rating. In some instances, there is a mismatch between the review and the rating. To identify the reviews with mismatched ratings we performed sentiment analysis using deep learning on Amazon.com product review data. Product reviews were converted to vectors using paragraph vector, which then was used to train a recurrent neural network with gated recurrent unit. Our model incorporated both semantic relationship of review text and product information. We also developed a w...

An Experimental Study of Feature Extraction Techniques in Opinion Mining J. Ashok Kumar and S. Abirami Anna University, India ABSTRACT The feature selection or extraction is the most important task in Opinion mining and Sentimental Analysis (OSMA) for calculating the polarity score. These scores are used to determine the positive, negative, and neutral polarity about the product, user reviews, user comments, and etc., in social media for the purpose of decision making and Business Intelligence to individuals or organizations. In this paper, we have performed an experimental study for different feature extraction or selection techniques available for opinion mining task. This experimental study is carried out in four stages. First, the data collection process has been done from readily available sources. Second, the pre-processing techniques are applied automatically using the tools to extract the terms, POS (Parts-of-Speech). Third, different feature selection or extraction techniq...