Sign in
Ctrl K

PuReGoMe

Understanding Dutch public sentiment during the COVID-19 outbreak period by analyzing real-time...

Dutch Public Reaction on Governmental COVID-19 Measures and Announcements

Public sentiment (the opinion, attitude or feeling that the public expresses) has been always attracting the attention of government, as it directly influences the implementation of policies. In the current epidemic situation, understanding the opinion of general public timely becomes even more important. However, the ‘staying-at-home’ policy makes face-to-face interactions and interviews challenging. Meanwhile, about 2.8 million users in the Netherlands use Twitter to share their opinions, making it a valuable platform for tracking and analyzing public sentiment. To understand the variation of Dutch public sentiment during the COVID-19 outbreak period, this project will analyze real-time Twitter data using machine learning and natural language processing approaches. Data collection will be based on COVID-19 related keywords and users. Its aim will be to provide a cost-effective and efficient way to access public reactions in a timely manner. For instance, instead of waiting for physical behaviours (like taking a walk outside) of people, their sentiment and intended behaviour could already be gleaned from Twitter data. Research team: Dr. Shihan Wang, Dr. Marijn Schraagen, Prof. Mehdi Dastani (Utrecht University)eScience Research Engineer: Dr. Erik Tjong Kim Sang

Participating organisations

Netherlands eScience Center
Utrecht University
Social Sciences & Humanities
Social Sciences & Humanities

Impact

Output

Team

SW
Shihan Wang
Principal investigator
Utrecht University
Erik Tjong Kim Sang
Research Software Engineer
Netherlands eScience Center
MS
Marijn Schraagen
Jisk Attema
Programme Manager
Netherlands eScience Center

Related projects

COVID-19 Grand Challenge

Assessing the suspicion and severity of COVID-19 in a CT scan

Updated 13 months ago
Finished

FAIR Data for CAPACITY

Statistical analyses and machine learning models: Insights about the relation between...

Updated 13 months ago
Finished

Retina COVID19

Real Time National Policy Adjustment and Evaluation on the Basis of a Computational Model for COVID19

Updated 13 months ago
Finished

TwiNL

Analysis of social media messages

Updated 13 months ago
Finished

Related software

PuReGoMe

PU

Analyzes social media messages for polarity and stance towards governmental COVID-19 measures

Updated 21 months ago
3