135 citations · 151 across the 2 of their papers we have counts for
4 papers
Addressing machine learning concept drift reveals declining vaccine sentiment during the COVID-19 pandemic
Martin Müller, Marcel Salathé
Social media analysis has become a common approach to assess public opinion on various topics, including those about health, in near real-time. The growing volume of social media p…
Clusters of science and health related Twitter users become more isolated during the COVID-19 pandemic
Francesco Durazzi, Martin Müller, Marcel Salathé +1
COVID-19 represents the most severe global crisis to date whose public conversation can be studied in real time. To do so, we use a data set of over 350 million tweets and retweets…
COVID-Twitter-BERT: A Natural Language Processing Model to Analyse COVID-19 Content on Twitter
Martin Müller, Marcel Salathé, Per E Kummervold
In this work, we release COVID-Twitter-BERT (CT-BERT), a transformer-based model, pretrained on a large corpus of Twitter messages on the topic of COVID-19. Our model shows a 10-30…
Crowdbreaks: Tracking Health Trends using Public Social Media Data and Crowdsourcing
Martin Mueller, Marcel Salathé
In the past decade, tracking health trends using social media data has shown great promise, due to a powerful combination of massive adoption of social media around the world, and…