Keyboard worriers

<?xml version="1.0" encoding="UTF-8" standalone="no"?>
<rdf:RDF xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance">
<rdf:Description>
<dc:creator>Ng, John </dc:creator>
<dc:creator>Zhang, Melanie</dc:creator>
<dc:date>2021-02-01</dc:date>
<dc:description xml:lang="es">Sumario: Twitter offers the public the opportunity to give their real-time thoughts on world events by posting short texts known as tweets'. The COVID-19 pandemic was the defining event of 2020, which makes it a great subject for sentiment analysis  the use of natural language processing to automatically determine the emotion a writer is expressing in a piece of text  or tweets. We wanted to see if we could use Twitter data relating to COVID-19 in the UK to uncover insights pertinent to public interest and the insurance industry. </dc:description>
<dc:identifier>https://documentacion.fundacionmapfre.org/documentacion/publico/es/bib/174802.do</dc:identifier>
<dc:language>eng</dc:language>
<dc:rights xml:lang="es">InC - http://rightsstatements.org/vocab/InC/1.0/</dc:rights>
<dc:subject xml:lang="es">Análisis de datos</dc:subject>
<dc:subject xml:lang="es">Comportamiento del consumidor</dc:subject>
<dc:subject xml:lang="es">COVID-19</dc:subject>
<dc:subject xml:lang="es">Pandemias</dc:subject>
<dc:subject xml:lang="es">Mercado de seguros</dc:subject>
<dc:type xml:lang="es">Artículos y capítulos</dc:type>
<dc:title xml:lang="es">Keyboard worriers</dc:title>
<dc:relation xml:lang="es">En: The Actuary : the magazine of the Institute & Faculty of Actuaries. - London :  Redactive Publishing, 2019-. - 01/02/2021 Número 1 - febrero 2021 , p. 27-29</dc:relation>
</rdf:Description>
</rdf:RDF>