Study of Coronavirus Impact on Parisian Population from April to June using Twitter and Text Mining Approach

Josimar Edinson Chire Saire; Jimy Frank Oblitas Cruz

doi:10.1109/ICS51289.2020.00056

Study of Coronavirus Impact on Parisian Population from April to June using Twitter and Text Mining Approach

Josimar Edinson Chire Saire
, Jimy Frank Oblitas Cruz

Dirección de Investigación, Innovación y Sostenibilidad de la UPN

Universidade de São Paulo

Producción científica: Capítulo del libro/informe/acta de congreso › Contribución a la conferencia › revisión exhaustiva

10 Citas (Scopus)

Resumen

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.

Idioma original	Inglés
Título de la publicación alojada	Proceedings - 2020 International Computer Symposium, ICS 2020
Páginas	242-246
Número de páginas	5
ISBN (versión digital)	9781728192550
DOI	https://doi.org/10.1109/ICS51289.2020.00056
Estado	Publicada - dic. 2020
Evento	2020 International Computer Symposium, ICS 2020 - Tainan, Taiwán Duración: 17 dic. 2020 → 19 dic. 2020

Serie de la publicación

Nombre	Proceedings - 2020 International Computer Symposium, ICS 2020

Conferencia

Conferencia	2020 International Computer Symposium, ICS 2020
País/Territorio	Taiwán
Ciudad	Tainan
Período	17/12/20 → 19/12/20

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Este resultado contribuye a los siguientes Objetivos de Desarrollo Sostenible

ODS 3: Salud y bienestar

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10.1109/ICS51289.2020.00056

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@inproceedings{0b719da81b82460b98ef30f23491a613,

title = "Study of Coronavirus Impact on Parisian Population from April to June using Twitter and Text Mining Approach",

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.",

keywords = "Coronavirus, Covid-19, Data mining, Data science, Europe, France, Infodemiology, Infoveillance, Natural Language Processing, Pandemic, Paris, People behaviour, Public Health, Sars-cov2, Social Networks, Text Mining, Twitter",

author = "\{Chire Saire\}, \{Josimar Edinson\} and \{Oblitas Cruz\}, \{Jimy Frank\}",

note = "Publisher Copyright: {\textcopyright} 2020 IEEE.; 2020 International Computer Symposium, ICS 2020 ; Conference date: 17-12-2020 Through 19-12-2020",

year = "2020",

month = dec,

doi = "10.1109/ICS51289.2020.00056",

language = "English",

series = "Proceedings - 2020 International Computer Symposium, ICS 2020",

pages = "242--246",

booktitle = "Proceedings - 2020 International Computer Symposium, ICS 2020",

}

Chire Saire, JE & Oblitas Cruz, JF 2020, Study of Coronavirus Impact on Parisian Population from April to June using Twitter and Text Mining Approach. En Proceedings - 2020 International Computer Symposium, ICS 2020., 9359027, Proceedings - 2020 International Computer Symposium, ICS 2020, pp. 242-246, 2020 International Computer Symposium, ICS 2020, Tainan, Taiwán, 17/12/20. https://doi.org/10.1109/ICS51289.2020.00056

Study of Coronavirus Impact on Parisian Population from April to June using Twitter and Text Mining Approach. / Chire Saire, Josimar Edinson; Oblitas Cruz, Jimy Frank.
Proceedings - 2020 International Computer Symposium, ICS 2020. 2020. p. 242-246 9359027 (Proceedings - 2020 International Computer Symposium, ICS 2020).

Producción científica: Capítulo del libro/informe/acta de congreso › Contribución a la conferencia › revisión exhaustiva

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T1 - Study of Coronavirus Impact on Parisian Population from April to June using Twitter and Text Mining Approach

AU - Chire Saire, Josimar Edinson

AU - Oblitas Cruz, Jimy Frank

PY - 2020/12

Y1 - 2020/12

N2 - 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.

AB - 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.

KW - Coronavirus

KW - Covid-19

KW - Data mining

KW - Data science

KW - Europe

KW - France

KW - Infodemiology

KW - Infoveillance

KW - Natural Language Processing

KW - Pandemic

KW - Paris

KW - People behaviour

KW - Public Health

KW - Sars-cov2

KW - Social Networks

KW - Text Mining

KW - Twitter

UR - https://www.scopus.com/pages/publications/85102193520

U2 - 10.1109/ICS51289.2020.00056

DO - 10.1109/ICS51289.2020.00056

M3 - Conference contribution

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T3 - Proceedings - 2020 International Computer Symposium, ICS 2020

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BT - Proceedings - 2020 International Computer Symposium, ICS 2020

T2 - 2020 International Computer Symposium, ICS 2020

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ER -

Study of Coronavirus Impact on Parisian Population from April to June using Twitter and Text Mining Approach

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