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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
2682020
Crowdbreaks: tracking health trends using public social media data and crowdsourcing
MM Müller, M Salathé
Frontiers in public health 7, 81, 2019
572019
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
382020
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
262020
Assessing Public Opinion on CRISPR-Cas9: Combining Crowdsourcing and Deep Learning
M Muller, M Schneider, M Salathé, E Vayena
BioRxiv, 802454, 2019
16*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
152020
Clusters of science and health related Twitter users become more isolated during the COVID-19 pandemic
F Durazzi, M Müller, M Salathé, D Remondini
Scientific reports 11 (1), 19655, 2021
132021
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
132019
Citizen science and online data: Opportunities and challenges for snake ecology and action against snakebite
AM Durso, RR de Castañeda, C Montalcini, MR Mondardini, ...
Toxicon: X 9, 100071, 2021
122021
Covid‐twitter‐BERT: A natural language processing model to analyse COVID‐19 content on twitter. CoRR
M Müller, M Salathé, PE Kummervold
92005
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
82020
COVID-Twitter-BERT: A Natural Language Processing Model to Analyse COVID-19 Content on Twitter.(2020)
M Müller, M Salathé, PE Kummervold
arXiv preprint cs.CL/2005.07503, 2020
52020
Cedille: A large autoregressive French language model
M Müller, F Laurent
arXiv preprint arXiv:2202.03371, 2022
22022
Summary of Tutorials at The Web Conference 2021
R West, S Bhagat, P Groth, M Zitnik, FM Couto, P Lisena, ...
Companion Proceedings of the Web Conference 2021, 727-733, 2021
22021
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
22020
On the use of applied machine learning and digital infrastructure to leverage social media data in health and epidemiology
MM Müller
EPFL, 2021
12021
SARS-CoV-2 ORF3c suppresses immune activation by inhibiting innate sensing
M Mueller, A Herrmann, S Fujita, EJ Kolberg, C Kruth, A Stange, ...
bioRxiv, 2023.02. 27.530232, 2023
2023
Underlying and Resulting Data of Sentiment Analysis on Tweets about CRISPR/Cas9
M Schneider, M Müller
ETH Zurich, 2019
2019
Group ID U13083 Affiliated authors Allémann, Chloé
O Altunina, O Balakiriev, S Bernard, P Borg, VG Boulanger, C Burger, ...
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