| Covid-twitter-bert: A natural language processing model to analyse covid-19 content on twitter M Müller, M Salathé, PE Kummervold arXiv preprint arXiv:2005.07503, 2020 | 48 | 2020 |
| Crowdbreaks: Tracking health trends using public social media data and crowdsourcing MM Müller, M Salathé Frontiers in public health 7, 81, 2019 | 22 | 2019 |
| Wet markets and food safety: TripAdvisor for improved global digital surveillance NE Kogan, I Bolon, N Ray, G Alcoba, JL Fernandez-Marquez, MM Müller, ... JMIR public health and surveillance 5 (2), e11477, 2019 | 6 | 2019 |
| Keep calm and carry on vaccinating: Is anti-vaccination sentiment contributing to declining vaccine coverage in England? M Edelstein, M Müller, S Ladhani, J Yarwood, M Salathé, M Ramsay Vaccine 38 (33), 5297-5304, 2020 | 5 | 2020 |
| Assessing Public Opinion on CRISPR-Cas9: Combining Crowdsourcing and Deep Learning M Muller, M Schneider, M Salathé, E Vayena BioRxiv, 802454, 2019 | 3* | 2019 |
| COVID-19 Misinformation Spread in Eight Countries: Exponential Growth Modeling Study EO Nsoesie, N Cesare, M Müller, A Ozonoff Journal of Medical Internet Research 22 (12), e24425, 2020 | 2 | 2020 |
| International expert communities on Twitter become more isolated during the COVID-19 pandemic F Durazzi, M Müller, M Salathé, D Remondini arXiv preprint arXiv:2011.06845, 2020 | 1 | 2020 |
| On the use of applied machine learning and digital infrastructure to leverage social media data in health and epidemiology MM Müller EPFL, 2021 | | 2021 |
| Addressing machine learning concept drift reveals declining vaccine sentiment during the COVID-19 pandemic M Müller, M Salathé arXiv preprint arXiv:2012.02197, 2020 | | 2020 |
| Characterizing the Spread of COVID-19 Misinformation in Eight Countries Using Exponential Growth Models. EO Nsoesie, N Cesare, M Müller, A Ozonoff Journal of Medical Internet Research, 2020 | | 2020 |
| Experts and authorities receive disproportionate attention on Twitter during the COVID-19 crisis K Gligorić, MH Ribeiro, M Müller, O Altunina, M Peyrard, M Salathé, ... arXiv preprint arXiv:2008.08364, 2020 | | 2020 |
| Underlying and Resulting Data of Sentiment Analysis on Tweets about CRISPR/Cas9 M Schneider, M Müller ETH Zurich, 2019 | | 2019 |
