RESEARCH PAPER ON SENTIMENTAL ANALYSIS OF ONLINE CUSTOMER REVIEWS AND RATING
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Abstract
Sentiment Analysis is the process of determining whether a part of writing is positive, negative or neutral. It is also known as opinion mining or emotion AI (Artificial Intelligence) and refers to the use of natural language processing, text analysis, and bio metrics to systematically identify, extract, quantify, and study effective states and subjective information. It is widely applied to voice of the customer materials such as reviews and survey responses, online and social media, and healthcare materials for applications that range from marketing to customer service to clinical medicine. In order to determine the sentiment of the overall document, we can use our own scoring algorithms – using the weighted phrases from the previous side, and then using our proprietary way of adding them up. By taking a set of content we can build a document-level sentiment classifier on it. In this thesis we are going to see how frequent item set can be used for mining reviews from online reviews posted by the customers. Our main aim is to create a system for analyzing sentiments or opinions which implies judgment of different consumer products.
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