Keyboard worriers

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<namePart>Zhang, Melanie</namePart>
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<abstract displayLabel="Summary">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. </abstract>
<note type="statement of responsibility">John Ng, Melanie Zhang</note>
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<topic>Análisis de datos</topic>
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<topic>Comportamiento del consumidor</topic>
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<topic>COVID-19</topic>
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<topic>Mercado de seguros</topic>
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<title>The Actuary : the magazine of the Institute & Faculty of Actuaries</title>
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<publisher>London :  Redactive Publishing, 2019-</publisher>
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<identifier type="local">MAP20200013259</identifier>
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<text>01/02/2021 Número 1 - febrero 2021 , p. 27-29</text>
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