About: Dutch General Public Reaction on Governmental COVID-19 Measures and Announcements in Twitter Data

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An Entity of Type : schema:ScholarlyArticle, within Data Space : wasabi.inria.fr associated with source document(s)

Attributes	Values
type	Academic Article research paper schema:ScholarlyArticle
isDefinedBy	Covid-on-the-Web dataset
title	Dutch General Public Reaction on Governmental COVID-19 Measures and Announcements in Twitter Data
Creator	Dastani, Mehdi Sang, Kim Schraagen, Marijn Tjong, Erik Wang, Shihan
source	ArXiv
abstract	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. 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 paper, 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 four months. We also identify public attitudes towards the Dutch policy on wearing face masks in a case study. 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.
has issue date	2020-06-12(xsd:dateTime)
has license	arxiv
sha1sum (hex)	15c3feb4397835f64be4394ce3c20d5529971b9c
resource representing a document's title	Dutch General Public Reaction on Governmental COVID-19 Measures and Announcements in Twitter Data
resource representing a document's body	covid:15c3feb4397835f64be4394ce3c20d5529971b9c#body_text
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