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Automated methods have been widely used to identify and analyze mental health conditions (e.g., depression) from various sources of information, including social media.
Language models are few-shot learners
Tom Brown, Benjamin Mann, Nick Ryder, Melanie Subbiah, Jared D Kaplan, Prafulla Dhariwal, Arvind Neelakantan, Pranav Shyam, Girish Sastry, Amanda Askell, Sandhini Agarwal, Ariel Herbert-Voss, Gretchen Krueger, Tom Henighan, Rewon Child, Aditya Ramesh, Daniel Ziegler, Jeffrey Wu, Clemens Winter, Chris Hesse, Mark Chen, Eric Sigler, Mateusz Litwin, Scott Gray, Benjamin Chess, Jack Clark, Christopher Berner, Sam McCandlish, Alec Radford, Ilya Sutskever, and Dario Amodei. 2020 · 1901
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The PHQ-9: validity of a brief depression severity measure
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The psychology of word use in depression forums in english and in spanish: Texting two text analytic approaches
Nairan Ramirez-Esparza, Cindy K Chung, Ewa Kacewicz, and James W Pennebaker. 2008 · 2008
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Twitter sentiment classification using distant supervision
Alec Go, Richa Bhayani, and Lei Huang. 2009 · 2009
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The psychological meaning of words: Liwc and computerized text analysis methods
Yla R Tausczik and James W Pennebaker. 2010 · 2010
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Underspecification presents challenges for credibility in modern machine learning
Alexander D’Amour, Katherine Heller, Dan Moldovan, Ben Adlam, Babak Alipanahi, Alex Beutel, Christina Chen, Jonathan Deaton, Jacob Eisenstein, Matthew D. Hoffman, Farhad Hormozdiari, Neil Houlsby, Shaobo Hou, Ghassen Jerfel, Alan Karthikesalingam, Mario Lucic, Yian Ma, Cory McLean, Diana Mincu, Akinori Mitani, Andrea Montanari, Zachary Nado, Vivek Natarajan, Christopher Nielson, Thomas F. Osborne, Rajiv Raman, Kim Ramasamy, Rory Sayres, Jessica Schrouff, Martin Seneviratne, Shannon Sequeira, Harini Suresh, Victor Veitch, Max Vladymyrov, Xuezhi Wang, Kellie Webster, Steve Yadlowsky, Taedong Yun, Xiaohua Zhai, and D. Sculley. 2020 · 2011
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Predicting depression via social media
Munmun De Choudhury, Michael Gamon, Scott Counts, and Eric Horvitz. 2013 · 2013
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Quantifying mental health signals in Twitter
Glen Coppersmith, Mark Dredze, and Craig Harman. 2014 · 2014
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The distress analysis interview corpus of human and computer interviews
Jonathan Gratch, Ron Artstein, Gale M Lucas, Giota Stratou, Stefan Scherer, Angela Nazarian, Rachel Wood, Jill Boberg, David DeVault, Stacy Marsella, et al. 2014 · 2014
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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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CLPsych 2016 shared task: Triaging content in online peer-support forums
David N. Milne, Glen Pink, Ben Hachey, and Rafael A. Calvo. 2016 · 2016
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Ethical research protocols for social media health research
Adrian Benton, Glen Coppersmith, and Mark Dredze. 2017 · 2017
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A deep semantic natural language processing platform
Matt Gardner, Joel Grus, Mark Neumann, Oyvind Tafjord, Pradeep Dasigi, Nelson H S Liu, Matthew E. Peters, Michael Schmitz, and Luke Zettlemoyer. 2017 · 2017
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Depression and self-harm risk assessment in online forums
Andrew Yates, Arman Cohan, and Nazli Goharian. 2017 · 2017
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Suicide risk and mental disorders
Louise Brådvik. 2018 · 2018
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Suicide risk and mental disorders
Louise Brådvik. 2018 · 2018
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Smhd: a large-scale resource for exploring online language usage for multiple mental health conditions
Arman Cohan, Bart Desmet, Andrew Yates, Luca Soldaini, Sean MacAvaney, and Nazli Goharian. 2018 · 2018
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Natural language processing of social media as screening for suicide risk
Glen Coppersmith, Ryan Leary, Patrick Crutchley, and A. Fine. 2018 · 2018
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Explainable prediction of medical codes from clinical text
James Mullenbach, Sarah Wiegreffe, Jon Duke, Jimeng Sun, and Jacob Eisenstein. 2018 · 2018
Suicide risk assessment with multi-level dual-context language and bert
Matthew Matero, Akash Idnani, Youngseo Son, Salvatore Giorgi, Huy Vu, Mohammad Zamani, Parth Limbachiya, Sharath Chandra Guntuku, and H Andrew Schwartz. 2019 · 2019
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Transfer learning in biomedical natural language processing: An evaluation of bert and elmo on ten benchmarking datasets
Yifan Peng, Shankai Yan, and Zhiyong Lu. 2019 · 2019
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CLPsych 2019 shared task: Predicting the degree of suicide risk in Reddit posts
Ayah Zirikly, Philip Resnik, Ozlem Uzuner, and Kristy Hollingshead. 2019 · 2019
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Towards explainability in using deep learning for the detection of anorexia in social media
Hessam Amini and Leila Kosseim. 2020 · 2020
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Shortcut learning in deep neural networks
Robert Geirhos, Jorn-Henrik Jacobsen, Claudio Michaelis, Richard Zemel, Wieland Brendel, Matthias Bethge, and Felix Wichmann. 2020 · 2020
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Cited alongside, same era.
Expert, crowdsourced, and machine assessment of suicide risk via online postings
Han-Chin Shing, Suraj Nair, Ayah Zirikly, Meir Friedenberg, Hal Daumé III, and Philip Resnik. 2018 · 2018
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Detecting linguistic traces of depression in topic-restricted text: Attending to self-stigmatized depression with nlp
Jt Wolohan, Misato Hiraga, Atreyee Mukherjee, Z. Sayyed, and Matthew Millard. 2018 · 2018
Cited alongside, same era.
Passive diagnosis incorporating the PHQ-4 for depression and anxiety
Fionn Delahunty, Robert Johansson, and Mihael Arcan. 2019 · 2019
Cited alongside, same era.
Bert: Pre-training of deep bidirectional transformers for language understanding
Jacob Devlin, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova. 2019a · 2019
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BERT: Pre-training of deep bidirectional transformers for language understanding
Jacob Devlin, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova. 2019b · 2019
Cited alongside, same era.
Methodological gaps in predicting mental health states from social media: Triangulating diagnostic signals
Sindhu Kiranmai Ernala, Michael L. Birnbaum, Kristin A. Candan, Asra F. Rizvi, William A. Sterling, John M. Kane, and Munmun De Choudhury. 2019 · 2019
Cited alongside, same era.
Do models of mental health based on social media data generalize?
Keith Harrigian, Carlos Aguirre, and Mark Dredze. 2020 · 2020
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Detection of mental health from reddit via deep contextualized representations
Zheng Ping Jiang, Sarah Ita Levitan, Jonathan Zomick, and Julia Hirschberg. 2020 · 2020
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Adapt or get left behind: Domain adaptation through bert language model finetuning for aspect-target sentiment classification
Alexander Rietzler, Sebastian Stabinger, Paul Opitz, and Stefan Engl. 2020 · 2020
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Predicting depression in screening interviews from latent categorization of interview prompts
Alex Rinaldi, Jean E Fox Tree, and Snigdha Chaturvedi. 2020 · 2020
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A prioritization model for suicidality risk assessment
Han-Chin Shing, Philip Resnik, and Douglas W Oard. 2020 · 2020
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Identifying depressive symptoms from tweets: Figurative language enabled multitask learning framework
Shweta Yadav, Jainish Chauhan, Joy Prakash Sain, Krishnaprasad Thirunarayan, Amit Sheth, and Jeremiah Schumm. 2020 · 2020
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On the state of social media data for mental health research
Keith Harrigian, Carlos Aguirre, and Mark Dredze. 2021 · 2021
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Micromodels for efficient, explainable, and reusable systems: A case study on mental health
Andrew Lee, Jonathan K. Kummerfeld, Larry An, and Rada Mihalcea. 2021 · 2021
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