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Sentiment Analysis from Bengali Depression Dataset using Machine Learning

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dc.contributor.author Khan, Md. Rafidul Hasan
dc.contributor.author Afroz, Umme Sunzida
dc.contributor.author Kaisar, Abu
dc.contributor.author Masum, Mohammad
dc.contributor.author Abujar, Sheikh
dc.contributor.author Hossain, Syed Akhter
dc.date.accessioned 2021-10-26T09:35:58Z
dc.date.available 2021-10-26T09:35:58Z
dc.date.issued 2020
dc.identifier.uri http://dspace.daffodilvarsity.edu.bd:8080/handle/123456789/6295
dc.description.abstract Nowadays, Sentiment Analysis is one of the advanced matters of natural language processing. Sentiment analysis determines a particular pole of a paragraph. Our purpose is to find the sentiment from the Bengali paragraph which is happy or sad using various types of machine learning classification analysis algorithms. For doing this we are collecting data from various social network sites, Bengali blogs, etc. To get a compatible result, we passed through many difficulties. Bengali text preprocessing is one of the complex parts of all. After preprocessing the data, we tokenized the data by using Countvectorizer. After that, we applied six different algorithms to predict almost high accuracy. Among them, the Multinomial Naive Bayes provide us the maximum accuracy which is 86.67% en_US
dc.language.iso en_US en_US
dc.publisher Scopus en_US
dc.subject Natural Language Processing en_US
dc.subject Sentiment Analysis en_US
dc.subject Depression Detection en_US
dc.subject Text Preprocessing en_US
dc.subject Social Media en_US
dc.subject Multinomial Naive Bayes en_US
dc.title Sentiment Analysis from Bengali Depression Dataset using Machine Learning en_US
dc.type Article en_US


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