2022
Sousa, R.; Oliveira, D.; Carneiro, A.; Pinto, L.; Pereira, A.; Peixoto, A.; Peixoto, H.; Machado, J.
The Covid-19 Influence on the Desire to Stay at Home: A Big Data Architecture Proceedings Article
Em: H., Tino P. Camacho D. Yin (Ed.): pp. 199-210, Springer Science and Business Media Deutschland GmbH, 2022, ISSN: 03029743, (cited By 0; Conference of 23rd International Conference on Intelligent Data Engineering and Automated Learning, IDEAL 2022 ; Conference Date: 24 November 2022 Through 26 November 2022; Conference Code:287419).
Resumo | Links | BibTeX | Etiquetas: Behavior analysis; Business-intelligence; Data architectures; Data tools; New case; Research focus; Stay at home, Big data, COVID-19
@inproceedings{Sousa2022199,
title = {The Covid-19 Influence on the Desire to Stay at Home: A Big Data Architecture},
author = {R. Sousa and D. Oliveira and A. Carneiro and L. Pinto and A. Pereira and A. Peixoto and H. Peixoto and J. Machado},
editor = {Tino P. Camacho D. Yin H.},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85144825704&doi=10.1007%2f978-3-031-21753-1_20&partnerID=40&md5=07933409c2e62457b481165cbb7438e0},
doi = {10.1007/978-3-031-21753-1_20},
issn = {03029743},
year = {2022},
date = {2022-01-01},
journal = {Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)},
volume = {13756 LNCS},
pages = {199-210},
publisher = {Springer Science and Business Media Deutschland GmbH},
abstract = {The COVID-19 pandemic has had an impact on many aspects of society in recent years. The ever-increasing number of daily cases and deaths makes people apprehensive about leaving their homes without a mask or going to crowded places for fear of becoming infected, especially when vaccination was not available. People were expected to respect confinement rules and have their public events cancelled as more restrictions were imposed. As a result of the pandemic’s insecurity and instability, people became more at ease at home, increasing their desire to stay at home. The present research focuses on studying the impact of the COVID-19 pandemic on the desire to stay at home and which metrics have a greater influence on this topic, using Big Data tools. It was possible to understand how the number of new cases and deaths influenced the desire to stay at home, as well as how the increase in vaccinations influenced it. Moreover, investigated how gatherings and confinement restrictions affected people’s desire to stay at home. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.},
note = {cited By 0; Conference of 23rd International Conference on Intelligent Data Engineering and Automated Learning, IDEAL 2022 ; Conference Date: 24 November 2022 Through 26 November 2022; Conference Code:287419},
keywords = {Behavior analysis; Business-intelligence; Data architectures; Data tools; New case; Research focus; Stay at home, Big data, COVID-19},
pubstate = {published},
tppubtype = {inproceedings}
}
The COVID-19 pandemic has had an impact on many aspects of society in recent years. The ever-increasing number of daily cases and deaths makes people apprehensive about leaving their homes without a mask or going to crowded places for fear of becoming infected, especially when vaccination was not available. People were expected to respect confinement rules and have their public events cancelled as more restrictions were imposed. As a result of the pandemic’s insecurity and instability, people became more at ease at home, increasing their desire to stay at home. The present research focuses on studying the impact of the COVID-19 pandemic on the desire to stay at home and which metrics have a greater influence on this topic, using Big Data tools. It was possible to understand how the number of new cases and deaths influenced the desire to stay at home, as well as how the increase in vaccinations influenced it. Moreover, investigated how gatherings and confinement restrictions affected people’s desire to stay at home. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.