IJDSBDA International Journal of Data Science and Big Data Analytics 2710-2599 SvedbergOpen ijdsbda-1-2-003 10.51483/IJDSBDA.1.2.2021.23-30 Research Paper Developing and testing a tool to classify sentiment analysis AcharyaSameer Kumar 1 * 1Data Science Department, NMIMS University, Mumbai, India. E-mail: sameeracharya.nmims@gmail.com *Corresponding author: Sameer Kumar Acharya, Data Science Department, NMIMS University, Mumbai, India. E-mail: sameeracharya.nmims@gmail.com 05 2021 1 2 23 30 Abstract

The era has faced with explosive growth in data generation. Data generation has undergone a renaissance change. This availability of data has led a paradigm shift in the E-commerce sector; data is no longer a by-product of business activities, but are the asset to a company it helps in providing insights which are required in satisfying customers’ needs. This paper provides an overview of sentiment analysis of product reviews based on different algorithms and its efficiency in determining positive from negative reviews based on N-gram, Bigram with the application of Count-Vectorizer and (Term Frequency-Inverse Document Frequency) (TFIDF) Matrix. Different classification models have been employed to check the prediction ) accuracy of the unlabeled text. Based on the above classification and tool has been developed which predicts the incoming reviews and classify its sentiment polarity.

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