Trust Based Predictive Analysis on E-Commerce Applications
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Abstract
One of the problems that online businesses platforms facing is gaining a greater understanding of the customer's thoughts and sentiments on the products. This problem can be solved by using sentiment analysis to derive additional insights from consumer feedback. Customer feedback provides a useful platform to discover a huge range of customer- initiated reactions to the product(s) that they have purchased. Text analytics provide businesses a more holistic picture of customer's satisfaction or dissatisfaction. It is insufficient to rely on customer's ratings alone to find out their experiences. This is because reviews can provide important feedback to businesses. In this paper, for text classification, we proposed the Naive Bayes algorithm. Despite its simplicity, it always outperforms much more complex solutions. The naive Bayes algorithm will be used in this paper to predict the mood of feedback. In the proposed plan, Natural language processing is used to extract features from the text of the feedback to train the algorithm.
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