Abstract
When buying a product people searches for several options on the internet so that they acquire only the best ones from the market. To assure this, people go to the internet and search for reviews. Based on the reviews the product will be chosen by the customers. When we think about this, there will be a lot of confusion which is the best one. To prevent this, reviews are rated and then they are categorized. Based on the classification the product is named as a good or bad product. To address the problem of classification we use SVM classification. SVM algorithm is chosen since it is easy and user-friendly. The Main aim of this work is finding the opinion of the product on marketing based on their reviews. Online reviews can help them improve the quality of services and products. However, it is an ambitious issue to take on valuable online reviews by realizing the review sentiment. This paper will dynamically determine the customer opinion about the specific product whether the customer will have an optimistic or bad opinion about the product. Online evaluations have transformed the vital resource of data for users prior to making an up-to-date purchase decision. Identifying evaluations is cooperative to check and run early endorsement and also reviewers are likely to be the buyers of a product.
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