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Capturing and analyzing social representations: a first application of Natural Language Processing techniques to reader’s comments in COVID-19 news

Subtitle: Argentina, 2020
Document type: Objeto de conferencia

Abstract

We present a first approximation to the quantification of social representations about the COVID-19, using news comments. A web crawler was developed to construct the dataset of reader’s comments. We detect relevant topics in the dataset using Latent Dirichlet Allocation, and analyze its evolution during time. Finally, we show a first prototype to the prediction of the majority topics, using FastText.

General information

Exposure date: octubre 2020
Issue date: 2020
Document language: English
Event: VI Simposio Argentino de Ciencia de Datos y GRANdes DAtos (AGRANDA 2020) - JAIIO 49 (Modalidad virtual)
Origin: Sociedad Argentina de Informática
ISSN: 2683-8966
Pages: 11-19
xmlui.dri2xhtml.METS-1.0.item-dc-subject: NLP ; News comments ; COVID-19 ; Social representations
Subjects: Ciencias Informáticas

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Created: 10 de marzo de 2021
Available since: 10 de marzo de 2021
Please, use one of this identificators(URI) for cite o linking this item:
  • http://sedici.unlp.edu.ar/handle/10915/114634

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    Creative Commons Attribution-NonCommercial-ShareAlike 3.0 Unported (CC BY-NC-SA 3.0) Except where otherwise noted, this item's license is described as Creative Commons Attribution-NonCommercial-ShareAlike 3.0 Unported (CC BY-NC-SA 3.0)