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- W4285221225 abstract "Sentiment analysis is the automatic extraction of positive or negative attitude expressions from textual information, and it has gotten a lot of interest from scholars in the last decade. Additionally, the popularity of online review sites, social networks, and personal blogs has grown rapidly in line with the advancement of technology; the users actively use on-line review sites, social networks, and personal blogs to express their opinions. They express people’s, organisations’, locations’, events’, and notions’ positive and negative sentiments. Natural language processing and machine learning, as well as other ways to working with massive amounts of text, have made it possible to start extracting sentiments from social media”. In this paper we will show the design of our social and media website along with different sentiment analysis algorithms like Naïve Bayes, LSTM and VADER; the analysis of these different algorithms will help us conclude for the most suitable algorithm to be applied in the social media website." @default.
- W4285221225 created "2022-07-14" @default.
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- W4285221225 date "2022-01-01" @default.
- W4285221225 modified "2023-09-27" @default.
- W4285221225 title "Sentiment Analysis in Social Media Website" @default.
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- W4285221225 doi "https://doi.org/10.1007/978-981-19-1122-4_56" @default.
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