@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",
}
