Approaches for Extracting Emotions from Customer Reviews Using Data Mining and Natural Language Processing

Abstract

There are a few interconnected steps in automatic opinion recognition: locating the limits of an opinion's expression, detecting its polarity, and quantifying its intensity. The research in this field has come a long way, but it still tries to focus on one of the previously mentioned issues at a time. As more and more people share their opinions online, automated information extraction to back up summaries of consumer reviews has become necessary. Most of us have traditionally placed a high value on the opinions of those around us while making important personal decisions. Many internet forums and forums gather and distribute the insights of many people from every part of the world. Viewing the many different perspectives presented on the web is tedious and difficult to make understanding. To make a knowledgeable decision quickly and easily, Opinion Mining collects and analyses feedback from consumers from multiple sources across the Internet. The proposed system's primary function is to synthesize feature-based summaries of product reviews provided by online store customers.