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Product Review Sentiment Analysis by Using NLP and Machine Learning in Bangla Language

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dc.contributor.author Shafin, Minhajul Abedin
dc.contributor.author Hasan, Md. Mehedi
dc.contributor.author Alam, Md. Rejaul
dc.contributor.author Mithu, Mosaddek Ali
dc.contributor.author Nur, Arafat Ulllah
dc.contributor.author Faruk, Md. Omar
dc.date.accessioned 2021-09-13T10:25:19Z
dc.date.available 2021-09-13T10:25:19Z
dc.date.issued 2020
dc.identifier.uri http://dspace.daffodilvarsity.edu.bd:8080/handle/123456789/6118
dc.description.abstract In this era of internet technology, in Bangladesh, online marketing or e-commerce businesses were already thriving. Due to the COVID-19 pandemic, as people are in lockdown, online shopping became the main platform for shopping as it is the safest way. It accelerated the businesses to come online. More online product service providers makes it better for people but also raises the question of product quality and services. So it is easy for new customers to get scammed while shopping online. Our goal is to make a system that will analyze the customer’s feedback from online shopping and provide a ratio of the positive and negative feedback written in Bangla from the previous customers using Natural Language Processing (NLP). We have collected over 1000 feedback and comments on the product to conduct the research. We used sentiment analysis along with some classification algorithms like KNN, Decision Tree, Support Vector Machine (SVM), Random Forest and Logistic Regression. With the highest accuracy of 88.81%, SVM outperformed all the other algorithms. en_US
dc.language.iso en_US en_US
dc.publisher Scopus en_US
dc.subject Machine Learning en_US
dc.subject Data Analysis en_US
dc.subject Sentiment Analysis en_US
dc.subject NLP en_US
dc.subject Classification en_US
dc.subject Prediction en_US
dc.subject SVM en_US
dc.title Product Review Sentiment Analysis by Using NLP and Machine Learning in Bangla Language en_US
dc.type Article en_US


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