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

Adeena Nasir; Munam Ali Shah; Ummarah Ashraf; Abid Khan; Gwanggil Jeon

doi:10.1016/j.compeleceng.2021.107526

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

Comput Electr Eng. 2021 Dec:96:107526. doi: 10.1016/j.compeleceng.2021.107526. Epub 2021 Oct 11.

Authors

Adeena Nasir¹, Munam Ali Shah¹, Ummarah Ashraf¹, Abid Khan², Gwanggil Jeon^{3

4}

Affiliations

¹ Department of Computer Science, COMSATS University Islamabad (CUI), Islamabad, Pakistan.
² School of Computing, Engineering & Digital Technologies, Teesside University, Tees Valley, TS1 3BX, Middlesbrough, UK.
³ School of Electronic Engineering, Xidian University, Xi'an, 710071, China.
⁴ Department of Embedded Systems Engineering, Incheon National University, Incheon, 22012, Republic of Korea.

Abstract

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.

Keywords: COVID-19; Coronavirus; Machine learning; Pandemic; Prediction; SARS-Cov-2; Sentiment analysis; Socioeconomic impact; Twitter.