Trustworthiness and Analysis of Sentiment of user’s Semantic Feedbacks in E-Commerce

Abstract

While Shopping Online Buyers mostly depend on reviews from users available on various websites. Trust is an important factor in any sort of relationship. A buyer can often see both the seller and the product, verify its quality, negotiate and bargain with the seller in traditional commerce. But in the context of online shopping, there is a absence of this face to face trust assessment. Absence of trust is always considered as an hurdle in online transactions. Ratings are available online. However those ratings are not always truthful. Then, they can falsify the weight and the scores .Semantic feedbacks make more sense than single scores. Our System aims at creating trust in online communities while giving action taking results .Those results such as trust weight, scores and the results of Sentiment Analysis help users to make a decision about purchasing particular product or not from an e-commerce application. Proposed design will use both ratings and semantic feedbacks to calculate trust weight and to classify comments and users.
DOI: 10.17762/ijritcc2321-8169.150270