An intelligent framework to predict socioeconomic impacts of COVID-19 and public sentiments()

The outbreak of novel coronavirus (COVID-19) has extremely shaken the whole world. COVID-19 has increased human distress, damaged the global economy, flipped the lives of many people around the world upside down, and has had a huge effect on the health, economic, environmental, and social sectors. T...

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Autores principales: Nasir, Adeena, Shah, Munam Ali, Ashraf, Ummarah, Khan, Abid, Jeon, Gwanggil
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier Ltd. 2021
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8502699/
https://www.ncbi.nlm.nih.gov/pubmed/34658455
http://dx.doi.org/10.1016/j.compeleceng.2021.107526
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author Nasir, Adeena
Shah, Munam Ali
Ashraf, Ummarah
Khan, Abid
Jeon, Gwanggil
author_facet Nasir, Adeena
Shah, Munam Ali
Ashraf, Ummarah
Khan, Abid
Jeon, Gwanggil
author_sort Nasir, Adeena
collection PubMed
description The outbreak of novel coronavirus (COVID-19) has extremely shaken the whole world. COVID-19 has increased human distress, damaged the global economy, flipped the lives of many people around the world upside down, and has had a huge effect on the health, economic, environmental, and social sectors. This study aims to determine the social and economic trends in the outbreak of COVID-19 in Pakistan. Machine learning techniques learn patterns from historical data and make predictions on its basis. Furthermore, an online survey has been conducted to collect data and a total of 410 responses are collected. Machine learning techniques have been used to highlight the impact of COVID-19 on daily life. Moreover, sentiment analysis on tweets of Pakistan has also been performed to evaluate the positive and negative sentiments of the people on COVID-19.
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spelling pubmed-85026992021-10-12 An intelligent framework to predict socioeconomic impacts of COVID-19 and public sentiments() Nasir, Adeena Shah, Munam Ali Ashraf, Ummarah Khan, Abid Jeon, Gwanggil Comput Electr Eng Article The outbreak of novel coronavirus (COVID-19) has extremely shaken the whole world. COVID-19 has increased human distress, damaged the global economy, flipped the lives of many people around the world upside down, and has had a huge effect on the health, economic, environmental, and social sectors. This study aims to determine the social and economic trends in the outbreak of COVID-19 in Pakistan. Machine learning techniques learn patterns from historical data and make predictions on its basis. Furthermore, an online survey has been conducted to collect data and a total of 410 responses are collected. Machine learning techniques have been used to highlight the impact of COVID-19 on daily life. Moreover, sentiment analysis on tweets of Pakistan has also been performed to evaluate the positive and negative sentiments of the people on COVID-19. Elsevier Ltd. 2021-12 2021-10-11 /pmc/articles/PMC8502699/ /pubmed/34658455 http://dx.doi.org/10.1016/j.compeleceng.2021.107526 Text en © 2021 Elsevier Ltd. All rights reserved. Since January 2020 Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID-19. The COVID-19 resource centre is hosted on Elsevier Connect, the company's public news and information website. Elsevier hereby grants permission to make all its COVID-19-related research that is available on the COVID-19 resource centre - including this research content - immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for free by Elsevier for as long as the COVID-19 resource centre remains active.
spellingShingle Article
Nasir, Adeena
Shah, Munam Ali
Ashraf, Ummarah
Khan, Abid
Jeon, Gwanggil
An intelligent framework to predict socioeconomic impacts of COVID-19 and public sentiments()
title An intelligent framework to predict socioeconomic impacts of COVID-19 and public sentiments()
title_full An intelligent framework to predict socioeconomic impacts of COVID-19 and public sentiments()
title_fullStr An intelligent framework to predict socioeconomic impacts of COVID-19 and public sentiments()
title_full_unstemmed An intelligent framework to predict socioeconomic impacts of COVID-19 and public sentiments()
title_short An intelligent framework to predict socioeconomic impacts of COVID-19 and public sentiments()
title_sort intelligent framework to predict socioeconomic impacts of covid-19 and public sentiments()
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8502699/
https://www.ncbi.nlm.nih.gov/pubmed/34658455
http://dx.doi.org/10.1016/j.compeleceng.2021.107526
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