Aspect based Fuzzy Logic Sentiment Analysis on Social Media Big Data
S. Uma Maheswari, S. S. Dhenakaran · 2020
Social Media is good information medium for disclosing information of products and services of E-Commerce Business. This information is provided by customers themselves on their purchased product. Aspect based sentiment analyzes of feature/specification quoted by the customers. Such specifications/reviews are available in Twitter, Flipkart websites. This research work considered reviews of features/specifications on Twitter and Flipkart websites. Hence this work focused on analyzing the problems of customer on buying quality products. This work is automated to extracts the semantic based aspects or features and their opinion for the task of analyzing comments. Fuzzy logic and NLP are employed in this work with consider all categories of comments to measure their given weightage by customer tweets. For experimentation real time Twitter data and Flipkart data has been used. Experimental result and performance analysis report proved that aspect based sentiment analysis on social data on this work is performing well. In this work hidden information about the product specification has been retrieved and produced concise information to customers perceives about the product specification and eases the customers to take decision on the purchase quality product. And also assist the business organization to take decision on the product specification and improve their business according to their customer's opinion and expectation.