Evaluating Performance on Covid-19 Tweet Sentiment Analysis Outbreak Using Support Vector Machine

M. Shanmuga Sundari; Pusarla Samyuktha; Alluri Kranthi; Suparna Das

doi:10.1007/978-981-16-9669-5_14

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Evaluating Performance on Covid-19 Tweet Sentiment Analysis Outbreak Using Support Vector Machine

M. Shanmuga Sundari Pusarla Samyuktha Alluri Kranthi Suparna Das

Year: 2022 Smart innovation, systems and technologies Pages: 151-159 Publisher: Springer Nature

DOI: 10.1007/978-981-16-9669-5_14

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Keywords:

Sentiment analysis Support vector machine Computer science Artificial intelligence Natural language processing Feeling Coronavirus disease 2019 (COVID-19) Machine learning Emotion detection Field (mathematics) Social media Process (computing) Text mining Emotion recognition Psychology World Wide Web Social psychology Mathematics

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3.28

FWCI (Field Weighted Citation Impact)

Refs

0.93

Citation Normalized Percentile

Is in top 1%

Is in top 10%

Citation History

Topics

Sentiment Analysis and Opinion Mining

Physical Sciences → Computer Science → Artificial Intelligence

Spam and Phishing Detection

Physical Sciences → Computer Science → Information Systems

Text and Document Classification Technologies

Physical Sciences → Computer Science → Artificial Intelligence

Evaluating Performance on Covid-19 Tweet Sentiment Analysis Outbreak Using Support Vector Machine

Metrics

Citation History

Topics

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