Abstract
AbstractIn the era of digitization, where everything is available online, and further, information about everything is online, we have transcended into a new phase—finding subjective information about everything in the form of reviews. Performing sentiment analysis on reviews left by customers can prove to be essential for service providers as it can help them engineer better products/services, understand sales dynamics, and target audiences appropriately. The more detailed the analysis, the deeper the insight gained. Due to this, sentiment analysis of online reviews has become a project taken up frequently, prompting data scientists to compile and share numerous data repositories. For this research, we have selected one such dataset consisting of reviews for several products and attempted to build an intelligent model using Bidirectional LSTM that can classify reviews as positive, negative, and neutral, rather than categorizing them only as positive and negative.
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