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Sentimental Analysis Applications and Approaches during COVID-19: A Survey

Published: 07 September 2021 Publication History

Abstract

The social media and electronic media has a vast amount of user-generated data such as people’ comment and reviews about different product, diseases, government policies etc. Sentimental analysis is the emerging field in text mining where people’s feeling and emotions are extracted using different techniques. COVID-19 has declared as pandemic and effected people’s lives all over the globe. It caused the feelings of fear, anxiety, anger, depression and many other psychological issues. In this survey paper, the sentimental analysis applications and methods which are used for COVID-19 research are briefly presented. The comparison of thirty primary studies shows that Naive Bayes and SVM are the widely used algorithms of sentimental analysis for COVID-19 research. The applications of sentimental analysis during COVID includes the analysis of people’s sentiments specially students, reopening sentiments, analysis of restaurants reviews and analysis of vaccine sentiments.

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  • (2024)The Concern of the European Citizens About Their Own and Family Health at the Beginning of Covid-19 Pandemic in May 2020Europe in the New World Economy: Opportunities and Challenges10.1007/978-3-031-71329-3_20(343-359)Online publication date: 26-Nov-2024
  • (2023)Sentimental Analysis of Arabic Tweets related to COVID-19 using AraBERT model2023 IEEE 12th International Conference on Communication Systems and Network Technologies (CSNT)10.1109/CSNT57126.2023.10134650(966-970)Online publication date: 8-Apr-2023
  • (2023)Vaccine sentiment analysis using BERT + NBSVM and geo-spatial approachesThe Journal of Supercomputing10.1007/s11227-023-05319-879:15(17355-17385)Online publication date: 7-May-2023
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cover image ACM Other conferences
IDEAS '21: Proceedings of the 25th International Database Engineering & Applications Symposium
July 2021
308 pages
ISBN:9781450389914
DOI:10.1145/3472163
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Published: 07 September 2021

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Author Tags

  1. Big Data
  2. COVID-19
  3. Coronavirus
  4. Machine Learning
  5. People’s reviews
  6. Sentimental Analysis
  7. Social Media

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IDEAS 2021

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Overall Acceptance Rate 74 of 210 submissions, 35%

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Cited By

View all
  • (2024)The Concern of the European Citizens About Their Own and Family Health at the Beginning of Covid-19 Pandemic in May 2020Europe in the New World Economy: Opportunities and Challenges10.1007/978-3-031-71329-3_20(343-359)Online publication date: 26-Nov-2024
  • (2023)Sentimental Analysis of Arabic Tweets related to COVID-19 using AraBERT model2023 IEEE 12th International Conference on Communication Systems and Network Technologies (CSNT)10.1109/CSNT57126.2023.10134650(966-970)Online publication date: 8-Apr-2023
  • (2023)Vaccine sentiment analysis using BERT + NBSVM and geo-spatial approachesThe Journal of Supercomputing10.1007/s11227-023-05319-879:15(17355-17385)Online publication date: 7-May-2023
  • (2023)Sentimental Analysis of COVID-19 Vaccine Tweets Using BERT+NBSVMMachine Learning and Principles and Practice of Knowledge Discovery in Databases10.1007/978-3-031-23618-1_16(238-247)Online publication date: 31-Jan-2023
  • (2022)Using High Performance Approaches to Covid-19 Vaccines Sentiment Analysis2022 30th Euromicro International Conference on Parallel, Distributed and Network-based Processing (PDP)10.1109/PDP55904.2022.00038(197-204)Online publication date: Mar-2022
  • (2022)Human sentiments monitoring during COVID-19 using AI-based modelingProcedia Computer Science10.1016/j.procs.2022.07.112203:C(753-758)Online publication date: 1-Jan-2022
  • (2022)Sentimental and spatial analysis of COVID-19 vaccines tweetsJournal of Intelligent Information Systems10.1007/s10844-022-00699-460:1(1-21)Online publication date: 15-Apr-2022
  • (2021)Artificial Intelligence Based Analysis of Positive and Negative Tweets Towards COVID-19 Vaccines2021 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)10.1109/BIBM52615.2021.9669140(3171-3177)Online publication date: 9-Dec-2021

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