A COVID-19 news coverage mood map of Europe

Frankie Robertson, Jarkko Lagus, Kaisla Kajava


Abstract
We present a COVID-19 news dashboard which visualizes sentiment in pandemic news coverage in different languages across Europe. The dashboard shows analyses for positive/neutral/negative sentiment and moral sentiment for news articles across countries and languages. First we extract news articles from news-crawl. Then we use a pre-trained multilingual BERT model for sentiment analysis of news article headlines and a dictionary and word vectors -based method for moral sentiment analysis of news articles. The resulting dashboard gives a unified overview of news events on COVID-19 news overall sentiment, and the region and language of publication from the period starting from the beginning of January 2020 to the end of January 2021.
Anthology ID:
2021.hackashop-1.15
Volume:
Proceedings of the EACL Hackashop on News Media Content Analysis and Automated Report Generation
Month:
April
Year:
2021
Address:
Online
Editors:
Hannu Toivonen, Michele Boggia
Venue:
Hackashop
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
110–115
Language:
URL:
https://aclanthology.org/2021.hackashop-1.15
DOI:
Bibkey:
Cite (ACL):
Frankie Robertson, Jarkko Lagus, and Kaisla Kajava. 2021. A COVID-19 news coverage mood map of Europe. In Proceedings of the EACL Hackashop on News Media Content Analysis and Automated Report Generation, pages 110–115, Online. Association for Computational Linguistics.
Cite (Informal):
A COVID-19 news coverage mood map of Europe (Robertson et al., Hackashop 2021)
Copy Citation:
PDF:
https://preview.aclanthology.org/nschneid-patch-3/2021.hackashop-1.15.pdf