Description
Metadata
Settings
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.
Permalink
an Entity references as follows:
Subject of Sentences In Document
Object of Sentences In Document
Explicit Coreferences
Implicit Coreferences
Graph IRI
Count
http://ns.inria.fr/covid19/graph/articles
3
Faceted Search & Find service v1.13.91
Alternative Linked Data Documents:
Sponger
|
ODE
Raw Data in:
CXML
|
CSV
| RDF (
N-Triples
N3/Turtle
JSON
XML
) | OData (
Atom
JSON
) | Microdata (
JSON
HTML
) |
JSON-LD
About
This work is licensed under a
Creative Commons Attribution-Share Alike 3.0 Unported License
.
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)
Copyright © 2009-2024 OpenLink Software