The E-commerce platform has provided the user and the organization with a new avenue for the product distribution and selling. The product distribution is greatly hampered by the opinions provided by the end user and if tampering and fake reviews are generated then it affects the product badly. The Natural language processing domain deals with the analysis of this review and provide the user with recommendation for decision making. The NLP domain deals with several issues like fake reviews, tampering with the reviews, and security for transfer of reviews etc. In this paper, a Blockchain based sentimental analysis module framework is proposed that provides the user with a secure and trustful environment for the opinions reviews as well as it provide a hybrid sentimental module that uses the algorithms from machine learning and deep learning for sentiment score generation. The Proposed Model was evaluated on different datasets of the varied domain. The proposed model performs a substantial improvement in providing the accurate results.

This paper proposes a natural language based feedback analysis system that extracts semantic relations from feedback data in order to map it with the domain ontology. After pre-processing a set of words or phrases are extracted from the input data. The data are analyzed semantically to interpret its meaning. This meaning is in an intermediate form which is then mapped to the terms defined in the ontology using similarity function. The opinion analysis of the semantic data is carried out for measuring the polarity of the feedback by the use of opinion analysis method. The system is evaluated on the input feedback data.