Public Sentiment on Governmental COVID-19 Measures in Dutch Social Media

Eintragsart
Autoren/Mitwirkende
Titel
Public Sentiment on Governmental COVID-19 Measures in Dutch Social Media
Zusammenfassung
Angaben zum Inhalt: „Public sentiment (the opinion, attitude or feeling that the public expresses) is a factor of interest for government, as it directly influences the implementation of policies. Given the unprecedented nature of the COVID-19 crisis, having an up-to-date representation of public sentiment on governmental measures and announcements is crucial. In this paper, we analyse Dutch public sentiment on governmental COVID-19 measures from text data collected across three online media sources (Twitter, Reddit and Nu.nl) from February to September 2020. We apply sentiment analysis methods to analyse polarity over time, as well as to identify stance towards two specific pandemic policies regarding social distancing and wearing face masks. The presented preliminary results provide valuable insights into the narratives shown in vast social media text data, which help understand the influence of COVID-19 measures on the general public.“
Datum
2020
Titel des Konferenzbandes
Proceedings of the 1st Workshop on NLP for COVID-19 (Part 2) at EMNLP 2020
Name der Konferenz
Proceedings of the 1st Workshop on NLP for COVID-19 (Part 2) at EMNLP 2020
Ort
Online
Verlag
Association for Computational Linguistics
Sprache
en
Zitierung
WANG, Shihan, Marijn SCHRAAGEN, Erik TJONG KIM SANG und Mehdi DASTANI, 2020. Public Sentiment on Governmental COVID-19 Measures in Dutch Social Media. In: Proceedings of the 1st Workshop on NLP for COVID-19 (Part 2) at EMNLP 2020 [online]. Online: Association for Computational Linguistics. 2020. Verfügbar unter: https://www.aclweb.org/anthology/2020.nlpcovid19-2.17