Dutch General Public Reaction on Governmental COVID-19 Measures and
Announcements in Twitter Data
- URL: http://arxiv.org/abs/2006.07283v3
- Date: Mon, 21 Dec 2020 19:53:55 GMT
- Title: Dutch General Public Reaction on Governmental COVID-19 Measures and
Announcements in Twitter Data
- Authors: Shihan Wang, Marijn Schraagen, Erik Tjong Kim Sang and Mehdi Dastani
- Abstract summary: We collect streaming data using the Twitter API starting from the COVID-19 outbreak in the Netherlands in February 2020.
We track Dutch general public reactions on governmental measures and announcements.
We provide temporal analysis of tweet frequency and public sentiment over the past seven months.
- Score: 1.7289766438701686
- License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
- Abstract: Public sentiment (the opinions, attitudes or feelings expressed by the
public) 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. While the 'staying-at-home' policy makes
face-to-face interactions and interviews challenging, analysing real-time
Twitter data that reflects public opinion toward policy measures is a
cost-effective way to access public sentiment. In this context, we collect
streaming data using the Twitter API starting from the COVID-19 outbreak in the
Netherlands in February 2020, and track Dutch general public reactions on
governmental measures and announcements. We provide temporal analysis of tweet
frequency and public sentiment over the past seven months. We also identify
public attitudes towards two Dutch policies in case studies: one regarding
social distancing and one regarding wearing face masks. By presenting those
preliminary results, we aim to provide visibility into the social media
discussions around COVID-19 to the general public, scientists and policy
makers. The data collection and analysis will be updated and expanded over
time.
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