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A user-generated text on social media enables health workers to keep track of information, identify possible outbreaks, forecast disease trends, monitor emergency cases, and ascertain disease awareness and response to official health correspondence.
Lei Cao, Huijun Zhang, Ling Feng, Zihan Wei, Xin Wang, Ningyun Li, and Xiaohao He. 2019 · 1910
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Distilbert, a distilled version of bert: smaller, faster, cheaper and lighter
Victor Sanh, Lysandre Debut, Julien Chaumond, and Thomas Wolf. 2019 · 1910
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Dreaddit: A reddit dataset for stress analysis in social media
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An inventory for measuring depression
Aaron T Beck, Calvin H Ward, Mock Mendelson, Jeremiah Mock, and John Erbaugh. 1961 · 1961
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ktrain: A low-code library for augmented machine learning
Arun S. Maiya. 2020 · 2004
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Covid-twitter-bert: A natural language processing model to analyse covid-19 content on twitter
Martin Müller, Marcel Salathé, and Per E Kummervold. 2020 · 2005
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Bertweet: A pre-trained language model for english tweets
Dat Quoc Nguyen, Thanh Vu, and Anh Tuan Nguyen. 2020 · 2005
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Syndromic surveillance: is it a useful tool for local outbreak detection?
Kirsty Hope, David N Durrheim, Edouard Tursan d’Espaignet, and Craig Dalton. 2006 · 2006
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Bioalbert: A simple and effective pre-trained language model for biomedical named entity recognition
Usman Naseem, Matloob Khushi, Vinay Reddy, Sakthivel Rajendran, Imran Razzak, and Jinman Kim. 2020 · 2009
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Explainable automated fact-checking for public health claims
Neema Kotonya and Francesca Toni. 2020 · 2010
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A model for mining public health topics from twitter
Michael J Paul and Mark Dredze. 2012 · 2012
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Adam: A method for stochastic optimization
Diederik P Kingma and Jimmy Ba. 2014 · 2014
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Using social media for actionable disease surveillance and outbreak management: a systematic literature review
Lauren E Charles-Smith, Tera L Reynolds, Mark A Cameron, Mike Conway, Eric HY Lau, Jennifer M Olsen, Julie A Pavlin, Mika Shigematsu, Laura C Streichert, Katie J Suda, et al. 2015 · 2015
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Systematic review on the prevalence, frequency and comparative value of adverse events data in social media
Su Golder, Gill Norman, and Yoon K Loke. 2015 · 2015
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Towards developing an annotation scheme for depressive disorder symptoms: A preliminary study using twitter data
Danielle L Mowery, Craig Bryan, and Mike Conway. 2015 · 2015
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Ups and downs: Modeling the visual evolution of fashion trends with one-class collaborative filtering
Ruining He and Julian McAuley. 2016 · 2016
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A test collection for research on depression and language use
David E Losada and Fabio Crestani. 2016 · 2016
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SemEval-2016 task 6: Detecting stance in tweets
Saif Mohammad, Svetlana Kiritchenko, Parinaz Sobhani, Xiaodan Zhu, and Colin Cherry. 2016 · 2016
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Systematic review of surveillance by social media platforms for illicit drug use
Donna M Kazemi, Brian Borsari, Maureen J Levine, and Beau Dooley. 2017 · 2017
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Social monitoring for public health
Biobert: a pre-trained biomedical language representation model for biomedical text mining
Jinhyuk Lee, Wonjin Yoon, Sungdong Kim, Donghyeon Kim, Sunkyu Kim, Chan Ho So, and Jaewoo Kang. 2019 · 2019
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Roberta: A robustly optimized bert pretraining approach
Yinhan Liu, Myle Ott, Naman Goyal, Jingfei Du, Mandar Joshi, Danqi Chen, Omer Levy, Mike Lewis, Luke Zettlemoyer, and Veselin Stoyanov. 2019 · 2019
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Crowdbreaks: Tracking health trends using public social media data and crowdsourcing
Martin M Müller and Marcel Salathé. 2019 · 2019
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Social media–and internet-based disease surveillance for public health
Allison E Aiello, Audrey Renson, and Paul N Zivich. 2020 · 2020
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Leveraging sentiment distributions to distinguish figurative from literal health reports on twitter
Rhys Biddle, Aditya Joshi, Shaowu Liu, Cecile Paris, and Guandong Xu. 2020 · 2020
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Michael J Paul and Mark Dredze. 2017 · 2017
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Cyclical learning rates for training neural networks
Leslie N Smith. 2017 · 2017
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Social media interventions for precision public health: promises and risks
Adam G Dunn, Kenneth D Mandl, and Enrico Coiera. 2018 · 2018
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Did you really just have a heart attack? towards robust detection of personal health mentions in social media
Payam Karisani and Eugene Agichtein. 2018 · 2018
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Identifying depression on reddit: The effect of training data
Inna Pirina and Çağrı Çöltekin. 2018 · 2018
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Overview of the third social media mining for health (SMM4H) shared tasks at EMNLP 2018
Davy Weissenbacher, Abeed Sarker, Michael J. Paul, and Graciela Gonzalez-Hernandez. 2018 · 2018
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BERT: Pre-training of deep bidirectional transformers for language understanding
Jacob Devlin, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova. 2019 · 2019
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Covidlies: Detecting covid-19 misinformation on social media
Tamanna Hossain, Robert L Logan IV, Arjuna Ugarte, Yoshitomo Matsubara, Sean Young, and Sameer Singh. 2020 · 2020
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A knowledge enhanced ensemble learning model for mental disorder detection on social media
Guozheng Rao, Chengxia Peng, Li Zhang, Xin Wang, and Zhiyong Feng. 2020 · 2020
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Sentiment analysis methods for hpv vaccines related tweets based on transfer learning
Li Zhang, Haimeng Fan, Chengxia Peng, Guozheng Rao, and Qing Cong. 2020 · 2020
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Mentalbert: Publicly available pretrained language models for mental healthcare
Shaoxiong Ji, Tianlin Zhang, Luna Ansari, Jie Fu, Prayag Tiwari, and Erik Cambria. 2021 · 2021
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Sad: A stress annotated dataset for recognizing everyday stressors in sms-like conversational systems
Matthew Louis Mauriello, Thierry Lincoln, Grace Hon, Dorien Simon, Dan Jurafsky, and Pablo Paredes. 2021 · 2021
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Towards ordinal suicide ideation detection on social media
Ramit Sawhney, Harshit Joshi, Saumya Gandhi, and Rajiv Ratn Shah. 2021 · 2021
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Early identification of depression severity levels on reddit using ordinal classification
Usman Naseem, Adam G. Dunn, Jinman Kim, and Matloob Khushi. 2022a · 2022
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Identification of disease or symptom terms in reddit to improve health mention classification
Usman Naseem, Jinman Kim, Matloob Khushi, and Adam G. Dunn. 2022b · 2022
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