Analysis of product Twitter data though opinion mining

Abstract

In recent years, there is a rapid growth in online communication. There are many social networking sites and related mobile applications, and some more are still emerging. Huge amount of data is generated by these sites everyday and this data can be used as a source for various analysis purposes. Twitter is one of the most popular networking sites with millions of users. There are users with different views and varieties of reviews in the form of tweets are generated by them. In this paper, we have concentrated on providing the opinion on the particular product using the Twitter data. There are millions of reviews on single product and it would be impossible for the customer or the organization to read each review and judge the quality of the product. This implementation paper provides the opinion mining on particular product based on reviews. The work includes determination of positivity, negativity of tweets and provides overall percentage of positive, negative and neutral tweets. The main idea behind this work is that the customer should automatically get suggestion about the product based on previous tweets. This implementation paper also provides effective decision making opinion to the customer and also provides feedback to the company to improve their product and business.