Study of coronavirus impact on parisian population from april to june using Twitter and text Mining Approach
Descripción del Articulo
ABSTRACT The fast spreading of coronavirus name covid19, generated the actual pandemic forcing to change daily activities. Health Councils of each country promote health policies, close borders and start a partial or total lockdown. One of the first countries in Europe with high impact was Italy. Be...
Autores: | , |
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Formato: | objeto de conferencia |
Fecha de Publicación: | 2020 |
Institución: | Universidad Privada del Norte |
Repositorio: | UPN-Institucional |
Lenguaje: | inglés |
OAI Identifier: | oai:repositorio.upn.edu.pe:11537/26914 |
Enlace del recurso: | https://hdl.handle.net/11537/26914 https://doi.org/10.1109/ICS51289.2020.00056 |
Nivel de acceso: | acceso abierto |
Materia: | Covid-19 Pandemia Redes sociales Impacto económico Francia https://purl.org/pe-repo/ocde/ford#2.11.04 |
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dc.title.es_PE.fl_str_mv |
Study of coronavirus impact on parisian population from april to june using Twitter and text Mining Approach |
title |
Study of coronavirus impact on parisian population from april to june using Twitter and text Mining Approach |
spellingShingle |
Study of coronavirus impact on parisian population from april to june using Twitter and text Mining Approach Chire Saire, Josimar Edinson Covid-19 Pandemia Redes sociales Impacto económico Francia https://purl.org/pe-repo/ocde/ford#2.11.04 |
title_short |
Study of coronavirus impact on parisian population from april to june using Twitter and text Mining Approach |
title_full |
Study of coronavirus impact on parisian population from april to june using Twitter and text Mining Approach |
title_fullStr |
Study of coronavirus impact on parisian population from april to june using Twitter and text Mining Approach |
title_full_unstemmed |
Study of coronavirus impact on parisian population from april to june using Twitter and text Mining Approach |
title_sort |
Study of coronavirus impact on parisian population from april to june using Twitter and text Mining Approach |
author |
Chire Saire, Josimar Edinson |
author_facet |
Chire Saire, Josimar Edinson Oblitas Cruz, Jimy Frank |
author_role |
author |
author2 |
Oblitas Cruz, Jimy Frank |
author2_role |
author |
dc.contributor.author.fl_str_mv |
Chire Saire, Josimar Edinson Oblitas Cruz, Jimy Frank |
dc.subject.es_PE.fl_str_mv |
Covid-19 Pandemia Redes sociales Impacto económico Francia |
topic |
Covid-19 Pandemia Redes sociales Impacto económico Francia https://purl.org/pe-repo/ocde/ford#2.11.04 |
dc.subject.ocde.es_PE.fl_str_mv |
https://purl.org/pe-repo/ocde/ford#2.11.04 |
description |
ABSTRACT The fast spreading of coronavirus name covid19, generated the actual pandemic forcing to change daily activities. Health Councils of each country promote health policies, close borders and start a partial or total lockdown. One of the first countries in Europe with high impact was Italy. Besides at the end of April, one country with a shared border was on the top of 10 countries with more total cases, then France started with its own battle to beat coronavirus. This paper studies the impact of coronavirus in the poopulation of Paris, France from April 23 to June 18, using Text Mining approach, processing data collected from Social Network and using trends related of searching. First finding is a decreasing pattern of publications/interest, and second is related to health crisis and economical impact generated by coronavirus. |
publishDate |
2020 |
dc.date.accessioned.none.fl_str_mv |
2021-06-21T17:30:55Z |
dc.date.available.none.fl_str_mv |
2021-06-21T17:30:55Z |
dc.date.issued.fl_str_mv |
2020-02-10 |
dc.type.es_PE.fl_str_mv |
info:eu-repo/semantics/conferenceObject |
format |
conferenceObject |
dc.identifier.citation.es_PE.fl_str_mv |
Chire, J. & Oblitas, J. (2020). Study of coronavirus impact on parisian population from april to june using Twitter and text Mining Approach. International Computer Symposium (ICS), 242-246. https://doi.org/10.1109/ICS51289.2020.00056 |
dc.identifier.uri.none.fl_str_mv |
https://hdl.handle.net/11537/26914 |
dc.identifier.journal.es_PE.fl_str_mv |
International Computer Symposium (ICS) |
dc.identifier.doi.none.fl_str_mv |
https://doi.org/10.1109/ICS51289.2020.00056 |
identifier_str_mv |
Chire, J. & Oblitas, J. (2020). Study of coronavirus impact on parisian population from april to june using Twitter and text Mining Approach. International Computer Symposium (ICS), 242-246. https://doi.org/10.1109/ICS51289.2020.00056 International Computer Symposium (ICS) |
url |
https://hdl.handle.net/11537/26914 https://doi.org/10.1109/ICS51289.2020.00056 |
dc.language.iso.es_PE.fl_str_mv |
eng |
language |
eng |
dc.rights.es_PE.fl_str_mv |
info:eu-repo/semantics/openAccess |
dc.rights.*.fl_str_mv |
Atribución-NoComercial-CompartirIgual 3.0 Estados Unidos de América |
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https://creativecommons.org/licenses/by-nc-sa/3.0/us/ |
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openAccess |
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Atribución-NoComercial-CompartirIgual 3.0 Estados Unidos de América https://creativecommons.org/licenses/by-nc-sa/3.0/us/ |
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application/pdf |
dc.publisher.es_PE.fl_str_mv |
IEEE |
dc.publisher.country.es_PE.fl_str_mv |
TW |
dc.source.es_PE.fl_str_mv |
Universidad Privada del Norte Repositorio Institucional - UPN |
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Chire Saire, Josimar EdinsonOblitas Cruz, Jimy Frank2021-06-21T17:30:55Z2021-06-21T17:30:55Z2020-02-10Chire, J. & Oblitas, J. (2020). Study of coronavirus impact on parisian population from april to june using Twitter and text Mining Approach. International Computer Symposium (ICS), 242-246. https://doi.org/10.1109/ICS51289.2020.00056https://hdl.handle.net/11537/26914International Computer Symposium (ICS)https://doi.org/10.1109/ICS51289.2020.00056ABSTRACT The fast spreading of coronavirus name covid19, generated the actual pandemic forcing to change daily activities. Health Councils of each country promote health policies, close borders and start a partial or total lockdown. One of the first countries in Europe with high impact was Italy. Besides at the end of April, one country with a shared border was on the top of 10 countries with more total cases, then France started with its own battle to beat coronavirus. This paper studies the impact of coronavirus in the poopulation of Paris, France from April 23 to June 18, using Text Mining approach, processing data collected from Social Network and using trends related of searching. 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La información contenida en este registro es de entera responsabilidad de la institución que gestiona el repositorio institucional donde esta contenido este documento o set de datos. El CONCYTEC no se hace responsable por los contenidos (publicaciones y/o datos) accesibles a través del Repositorio Nacional Digital de Ciencia, Tecnología e Innovación de Acceso Abierto (ALICIA).