Suggestion Mining from Customer Reviews

The increasing online content has influenced users’ buying behavior. It has triggered a paradigm shift in marketing strategies, as the consumer is no longer swayed by marketers, instead relying on user comments for a particular product or service. This paper focuses on extracting information from feedbacks like suggestions and recommendation by the users that is often present along with the sentiment. While Sentiment Analysis looks at extraction of consumer sentiment, our focus is on extracting actionable feedback present in the text for use by different stakeholders like business analysts and the customer. Our focus is on mining the key suggestions present in text which would benefit the product developer. We present our results and observations in the paper.