Martin M Müller
Cited by
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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
Crowdbreaks: Tracking health trends using public social media data and crowdsourcing
MM Müller, M Salathé
Frontiers in public health 7, 81, 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
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
Assessing Public Opinion on CRISPR-Cas9: Combining Crowdsourcing and Deep Learning
M Muller, M Schneider, M Salathé, E Vayena
BioRxiv, 802454, 2019
Addressing machine learning concept drift reveals declining vaccine sentiment during the COVID-19 pandemic
M Müller, M Salathé
arXiv preprint arXiv:2012.02197, 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
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
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
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
Underlying and Resulting Data of Sentiment Analysis on Tweets about CRISPR/Cas9
M Schneider, M Müller
ETH Zurich, 2019
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