About: The epidemiological outbreak of a novel coronavirus (2019-nCoV or Covid-19) in China, and its rapid spread, gave rise to the first pandemic in the digital age. Derived from this fact that has surprised humanity, many countries started with different strategies in order to stop the infection. In this context, one of the greatest challenges for the scientific community is monitoring (real time) the global population to get immediate feedback of what is happening with the people during this public health contingency. An alternative interesting and affordable for the materialization of the aforementioned are the social networks. In a social network, the persons can act as sensors/information not only of personal data but also data derived from their behavior. This paper aims to analyze the publications of people in Mexico using a Text Mining approach. Specifically, Mexico City is presented as a case study to help understand the impact on society of the spread of Covid-19.

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

About: The epidemiological outbreak of a novel coronavirus (2019-nCoV or Covid-19) in China, and its rapid spread, gave rise to the first pandemic in the digital age. Derived from this fact that has surprised humanity, many countries started with different strategies in order to stop the infection. In this context, one of the greatest challenges for the scientific community is monitoring (real time) the global population to get immediate feedback of what is happening with the people during this public health contingency. An alternative interesting and affordable for the materialization of the aforementioned are the social networks. In a social network, the persons can act as sensors/information not only of personal data but also data derived from their behavior. This paper aims to analyze the publications of people in Mexico using a Text Mining approach. Specifically, Mexico City is presented as a case study to help understand the impact on society of the spread of Covid-19. Goto Sponge NotDistinct Permalink

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

Attributes	Values
type	abstract
value	The epidemiological outbreak of a novel coronavirus (2019-nCoV or Covid-19) in China, and its rapid spread, gave rise to the first pandemic in the digital age. Derived from this fact that has surprised humanity, many countries started with different strategies in order to stop the infection. In this context, one of the greatest challenges for the scientific community is monitoring (real time) the global population to get immediate feedback of what is happening with the people during this public health contingency. An alternative interesting and affordable for the materialization of the aforementioned are the social networks. In a social network, the persons can act as sensors/information not only of personal data but also data derived from their behavior. This paper aims to analyze the publications of people in Mexico using a Text Mining approach. Specifically, Mexico City is presented as a case study to help understand the impact on society of the spread of Covid-19.
part of	Text Mining Approach to Analyze Coronavirus Impact: Mexico City as Case of Study
is abstract of	Text Mining Approach to Analyze Coronavirus Impact: Mexico City as Case of Study

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