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

Facets (new session)
Description
Metadata
Settings
- owl:sameAs
- Inference Rule:

About: Study of Coronavirus Impact on Parisian Population from April to June using Twitter and Text Mining Approach Goto Sponge NotDistinct Permalink

An Entity of Type : schema:ScholarlyArticle, within Data Space : covidontheweb.inria.fr associated with source document(s)

Attributes	Values
type	Academic Article research paper schema:ScholarlyArticle
isDefinedBy	Covid-on-the-Web dataset
has title	Study of Coronavirus Impact on Parisian Population from April to June using Twitter and Text Mining Approach
Creator	Cruz, Oblitas Frank, Jimy
topic	covid:d3966711f4fc0a9b0bf75d928a3c02fe5ed422e5#this
Source	MedRxiv
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.
has issue date	2020-08-18(xsd:dateTime)
bibo:doi	10.1101/2020.08.15.20175810
has license	medrxiv
sha1sum (hex)	d3966711f4fc0a9b0bf75d928a3c02fe5ed422e5
schema:url	https://doi.org/10.1101/2020.08.15.20175810
resource representing a document's title	Study of Coronavirus Impact on Parisian Population from April to June using Twitter and Text Mining Approach
resource representing a document's body	covid:d3966711f4fc0a9b0bf75d928a3c02fe5ed422e5#body_text
is http://vocab.deri.ie/void#inDataset of	https://covidontheweb.inria.fr:4443/about/id/http/ns.inria.fr/covid19/d3966711f4fc0a9b0bf75d928a3c02fe5ed422e5
is schema:about of	named entity 'border' named entity 'health' named entity 'lockdown' named entity 'TEXT MINING' named entity 'IS A' named entity 'DECREASING' named entity 'TRENDS' named entity 'IMPACT' named entity 'SECOND' named entity 'generated' named entity 'studies' named entity 'promote' named entity 'pandemic' named entity 'coronavirus' named entity 'high' named entity 'Coronavirus' named entity 'coronavirus' named entity 'coronavirus' named entity 'health policies' named entity 'coronavirus' named entity 'Text Mining' named entity 'health crisis' named entity 'Text Mining' named entity 'COVID' named entity 'data collection' named entity 'social media' named entity 'COVID' named entity 'preprint' named entity 'global economy' named entity 'preprint' named entity 'Twitter' named entity 'Twitter' named entity 'preprint' named entity 'public health' named entity 'Data Mining' named entity 'economic crisis and recession' named entity 'covid19' named entity 'Internet' named entity 'adverse effect' named entity 'medRxiv' named entity 'medRxiv' named entity 'travel and tourism sector' named entity 'COVID 19' named entity 'Paris' named entity 'Twitter' named entity 'medRxiv' named entity 'supply and demand' named entity 'virus' named entity 'preprint' named entity 'COVID-19 outbreak' named entity 'COVID-19' named entity 'social network' named entity 'flattening the curve' named entity 'preprint' named entity 'World Bank' named entity 'self-isolation' named entity 'preprint' named entity 'Social distancing' named entity 'public health' named entity 'Twitter' named entity 'Paris' named entity 'WHO' named entity 'Italy' named entity 'preprint' named entity 'coronavirus' named entity 'preprint' named entity 'quarantine' named entity 'mortality rates' named entity 'Text Mining' named entity 'mental health' named entity 'preprint' named entity 'coronavirus infection' named entity 'government institutions' named entity 'COVID' named entity 'global economy' named entity 'global economy' named entity 'API' named entity 'Twitter' named entity 'CC-BY-NC-ND 4.0' named entity 'France' named entity 'France' named entity 'France'

Faceted Search & Find service v1.13.91 as of Mar 24 2020

Alternative Linked Data Documents: Sponger | ODE Content Formats:

RDF

ODATA

Microdata

About

OpenLink Virtuoso version 07.20.3229 as of Jul 10 2020, on Linux (x86_64-pc-linux-gnu), Single-Server Edition (94 GB total memory)
Data on this page belongs to its respective rights holders.
Virtuoso Faceted Browser Copyright © 2009-2024 OpenLink Software