Sentimental analysis of Twitter data and Comparison of covid 19 Cases trend Using Machine learning algorithms
3rd IEEE Global Conference for Advancement in Technology, GCAT 2022
; 2022.
Article
in English
| Scopus | ID: covidwho-2191784
ABSTRACT
Coronavirus was first detected in the year 2019 in Wuhan, China. The disease rapidly spread across the country in a short span of time. The Government had imposed strict rules and restrictions for lockdown and social distancing, work from home, and online classes to prevent the further spread of these covid cases During this phase, the morality of the covid cases was significantly controlled. But the larger population was affected by this. So, the mindset of the people has been changed. Sentimental analysis is an opinion mining approach to NLP which is used to detect and categorize the data as positive, negative, and neutral. In a situation like the COVID pandemic, one must stay in a positive mindset. In our project, we are implementing sentimental analysis using the Random Forest algorithm along with comparing the trend in variation of COVID 19 cases using the LSTM and KNN algorithms. © 2022 IEEE.
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Collection:
Databases of international organizations
Database:
Scopus
Language:
English
Journal:
3rd IEEE Global Conference for Advancement in Technology, GCAT 2022
Year:
2022
Document Type:
Article
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