PuReGoMe
Analyzes social media messages for polarity and stance towards governmental COVID-19 measures
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
Assessing the suspicion and severity of COVID-19 in a CT scan
Statistical analyses and machine learning models: Insights about the relation between...
Real Time National Policy Adjustment and Evaluation on the Basis of a Computational Model for COVID19
Analysis of social media messages
Analyzes social media messages for polarity and stance towards governmental COVID-19 measures