Measuring Shifts in Attitudes Towards COVID-19 Measures in Belgium Using Multilingual BERT
We classify seven months' worth of Belgian COVID-related Tweets using multilingual BERT and relate them to their governments' COVID measures. We classify Tweets by their stated opinion on Belgian government curfew measures (too strict, ok, too loose). We examine the change in topics discussed and views expressed over time and in reference to dates of related events such as implementation of new measures or COVID-19 related announcements in the media.
Code (1)
Methods 이 논문이 사용한 방법론
Similar Papers 제목 키워드 기반
Assessing the impact of forced and voluntary behavioral changes on economic-epidemiological co-dynamics: A comparative case study between Belgium and Sweden during the 2020 COVID-19 pandemic
During the COVID-19 pandemic, governments faced the challenge of managing population behavior to prevent their healthcare systems from collapsing. Sweden adopted a strategy centered on voluntary sanitary recommendations …
Covid-19 Belgium: Extended SEIR-QD model with nursing homes and long-term scenarios-based forecasts
Following the spread of the COVID-19 pandemic and pending the establishment of vaccination campaigns, several non pharmaceutical interventions such as partial and full lockdown, quarantine and measures of physical distan…
Dutch General Public Reaction on Governmental COVID-19 Measures and Announcements in Twitter Data
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…
Dynamics of the COVID-1 -- Comparison between the Theoretical Predictions and the Real Data, and Predictions about Returning to Normal Life
A new coronavirus disease, called COVID-19, appeared in the Chinese region of Wuhan at the end of last year; since then the virus spread to other countries, including most of Europe. We propose a differential equation go…
Validating a dynamic input-output model for the propagation of supply and demand shocks during the COVID-19 pandemic in Belgium
This work validates a dynamic production network model, used to quantify the impact of economic shocks caused by COVID-19 in the UK, using data for Belgium. Because the model was published early during the 2020 COVID-19 …
Time Series