Author : Vidhu Chaudhary 1
Date of Publication :30th November 2021
Abstract: The online market is always in demand, and every product's success rate is determined by how successful it is in the market, which is determined by consumer satisfaction and turnover. The effective utilization of the online platform in market crusades in the course of recent many years has roused the incorporation of web-based media stages like Facebook and another platform as a basic piece of the marketing platform and reviews of a product. Marketing Analysis investigators are progressively going to Facebook and other platforms as a sign of customer opinion assessment. We are keen on figuring out how certain and negative assessments engender through Facebook and how significant occasions impact product market success assessment. In this paper, we present a neural network-based method to deal with the breakdown of the opinion communicated on market analysis. To start with, our methodology addresses the text by thick vectors including sub-word data to more readily identify word similitude by taking advantage of both morphology and semantics. Then, at that point, a neural method is prepared to figure out how to order tweets relying upon feeling, in light of an accessible marked dataset. At last, the model is applied to play out the opinion investigation of an assortment of posts recovered during the days preceding the most recent analysis and posts
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