Study of coronavirus impact on parisian population from april to june using Twitter and text Mining Approach

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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...

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Detalles Bibliográficos
Autores: Chire Saire, Josimar Edinson, Oblitas Cruz, Jimy Frank
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
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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
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dc.rights.*.fl_str_mv Atribución-NoComercial-CompartirIgual 3.0 Estados Unidos de América
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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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spelling 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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