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- W3046541629 abstract "As we know, On February 11, 2020, the World Health Organization declared the official name for the illness thatis causing the 2019 novel corona virus episode, first recognized in Wuhan China. More than 216 countries areinfluenced so far, raising worries of broad dread and expanding tension in people exposed to the danger of theinfection. In the 20th century, internet user's who are using social network platforms growing exponentially andgetting benefited in the form of information gathering coming from all over the world by using the social networkplatform like twitter. In the current scenario, many researchers/scientists are working on sentiments of text onsocial network data shared by internet or social network users. In the form of text (tweets) on the twitter platform,people from all over the world are sharing the challenges of this COVID 19 epidemic in their feeling or opinions.Tweets in the form of text shared on twitter, we extracted the sentiments of the text (tweets) and analyze thesesentiments by using the Machine learning algorithm. We can predict the positive, negative, or neutral sentiments(emotions) of the people affected by the COVID 19 epidemic. From, our analyzed sentiment of textual datashared on twitter. We can protect our friends, relatives, and followers on social networks from their depressive ornegative behaviour using some preventive measures for which working class peoples are being negative." @default.
- W3046541629 created "2020-08-07" @default.
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- W3046541629 date "2020-01-01" @default.
- W3046541629 modified "2023-09-23" @default.
- W3046541629 title "SENTIMENT ANALYSIS OF COVID-19 EPIDEMIC USING MACHINE LEARNING ALGORITHMS ONTWITTER -" @default.
- W3046541629 hasPublicationYear "2020" @default.
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