Martin Müller
Martin Müller
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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
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
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
On the use of applied machine learning and digital infrastructure to leverage social media data in health and epidemiology
MM Müller
EPFL, 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
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
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
Underlying and Resulting Data of Sentiment Analysis on Tweets about CRISPR/Cas9
M Schneider, M Müller
ETH Zurich, 2019
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