Mining aspects on the social network

Abstract

This paper proposes an effective concept of mining the feedback of product given by the user. In return various solutions are suggested according to the ratings of the aspect and its corresponding weightage. The satisfaction of user is determined by the help of user’s rating and weight of the aspect determines the significance of each aspect in the user’s review. These methodologies are thus, important and play a significant role for the manufacturers and producers to improvise their product and eventually leading to rise in the market value of that particular product. The methodology here extracts the aspects from the feedbacks of users with the help of conditional probability and bootstrap technique. Also an approach that is supervised and is called by the name, Naïve Bayes is used to classify aspect ratings and the sentiment words are considered as properties or features.