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- W4307648809 abstract "The world is mutating into a better place due to the innovations happening around the globe. Since people spend much time regularly on social media to express their opinions, social networks are the primary sources of information regarding people’s opinions and feelings on various topics. Twitter is a micro blogging and social networking site that allows users to post brief status updates of up to 140 characters in length. It is a rapidly growing service. This project resolves the issue of sentiment analysis on Twitter. Sentiment analysis is a form of natural language processing used to monitor public opinion on a specific product or subject. Sentiment analysis, also known as opinion mining, entails creating a framework to capture and analyze product opinions expressed in blog posts, comments, reviews, or tweets. The objective of this report is to provide an illustration of this fascinating problem as well as a model for performing sentiment analysis on Twitter tweets using the Naïve Bayes classification algorithm." @default.
- W4307648809 created "2022-11-04" @default.
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- W4307648809 date "2022-10-28" @default.
- W4307648809 modified "2023-09-27" @default.
- W4307648809 title "A Novel Twitter Sentimental Analysis Approach Using Naive Bayes Classification" @default.
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- W4307648809 doi "https://doi.org/10.1007/978-981-19-4863-3_39" @default.
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