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A Survey on COVID-19 Data Analysis Using AI, IoT, and Social Media
Coronaviruses are a well-established and deadly group of viruses that cause illness in both humans and animals. The novel type of this virus group, named COVID-19, was firstly reported in December 2019, and, with the passage of time, coronavirus has spread to almost all parts of the world. Coronavir...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10303179/ https://www.ncbi.nlm.nih.gov/pubmed/37420714 http://dx.doi.org/10.3390/s23125543 |
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author | Butt, Muhammad Junaid Malik, Ahmad Kamran Qamar, Nafees Yar, Samad Malik, Arif Jamal Rauf, Usman |
author_facet | Butt, Muhammad Junaid Malik, Ahmad Kamran Qamar, Nafees Yar, Samad Malik, Arif Jamal Rauf, Usman |
author_sort | Butt, Muhammad Junaid |
collection | PubMed |
description | Coronaviruses are a well-established and deadly group of viruses that cause illness in both humans and animals. The novel type of this virus group, named COVID-19, was firstly reported in December 2019, and, with the passage of time, coronavirus has spread to almost all parts of the world. Coronavirus has been the cause of millions of deaths around the world. Furthermore, many countries are struggling with COVID-19 and have experimented with various kinds of vaccines to eliminate the deadly virus and its variants. This survey deals with COVID-19 data analysis and its impact on human social life. Data analysis and information related to coronavirus can greatly help scientists and governments in controlling the spread and symptoms of the deadly coronavirus. In this survey, we cover many areas of discussion related to COVID-19 data analysis, such as how artificial intelligence, along with machine learning, deep learning, and IoT, have worked together to fight against COVID-19. We also discuss artificial intelligence and IoT techniques used to forecast, detect, and diagnose patients of the novel coronavirus. Moreover, this survey also describes how fake news, doctored results, and conspiracy theories were spread over social media sites, such as Twitter, by applying various social network analysis and sentimental analysis techniques. A comprehensive comparative analysis of existing techniques has also been conducted. In the end, the Discussion section presents different data analysis techniques, provides future directions for research, and suggests general guidelines for handling coronavirus, as well as changing work and life conditions. |
format | Online Article Text |
id | pubmed-10303179 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-103031792023-06-29 A Survey on COVID-19 Data Analysis Using AI, IoT, and Social Media Butt, Muhammad Junaid Malik, Ahmad Kamran Qamar, Nafees Yar, Samad Malik, Arif Jamal Rauf, Usman Sensors (Basel) Review Coronaviruses are a well-established and deadly group of viruses that cause illness in both humans and animals. The novel type of this virus group, named COVID-19, was firstly reported in December 2019, and, with the passage of time, coronavirus has spread to almost all parts of the world. Coronavirus has been the cause of millions of deaths around the world. Furthermore, many countries are struggling with COVID-19 and have experimented with various kinds of vaccines to eliminate the deadly virus and its variants. This survey deals with COVID-19 data analysis and its impact on human social life. Data analysis and information related to coronavirus can greatly help scientists and governments in controlling the spread and symptoms of the deadly coronavirus. In this survey, we cover many areas of discussion related to COVID-19 data analysis, such as how artificial intelligence, along with machine learning, deep learning, and IoT, have worked together to fight against COVID-19. We also discuss artificial intelligence and IoT techniques used to forecast, detect, and diagnose patients of the novel coronavirus. Moreover, this survey also describes how fake news, doctored results, and conspiracy theories were spread over social media sites, such as Twitter, by applying various social network analysis and sentimental analysis techniques. A comprehensive comparative analysis of existing techniques has also been conducted. In the end, the Discussion section presents different data analysis techniques, provides future directions for research, and suggests general guidelines for handling coronavirus, as well as changing work and life conditions. MDPI 2023-06-13 /pmc/articles/PMC10303179/ /pubmed/37420714 http://dx.doi.org/10.3390/s23125543 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Review Butt, Muhammad Junaid Malik, Ahmad Kamran Qamar, Nafees Yar, Samad Malik, Arif Jamal Rauf, Usman A Survey on COVID-19 Data Analysis Using AI, IoT, and Social Media |
title | A Survey on COVID-19 Data Analysis Using AI, IoT, and Social Media |
title_full | A Survey on COVID-19 Data Analysis Using AI, IoT, and Social Media |
title_fullStr | A Survey on COVID-19 Data Analysis Using AI, IoT, and Social Media |
title_full_unstemmed | A Survey on COVID-19 Data Analysis Using AI, IoT, and Social Media |
title_short | A Survey on COVID-19 Data Analysis Using AI, IoT, and Social Media |
title_sort | survey on covid-19 data analysis using ai, iot, and social media |
topic | Review |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10303179/ https://www.ncbi.nlm.nih.gov/pubmed/37420714 http://dx.doi.org/10.3390/s23125543 |
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