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Very large language models (LLMs) perform extremely well on a spectrum of NLP tasks in a zero-shot setting.
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Automatic recognition of personality in conversation
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Exploratory factor analysis
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Predicting personality with social media
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The big five personality traits, learning styles, and academic achievement
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Private traits and attributes are predictable from digital records of human behavior
M. Kosinski, D. Stillwell, and T. Graepel. 2013 · 2013
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Personality, gender, and age in the language of social media: The open-vocabulary approach
H Andrew Schwartz, Johannes C Eichstaedt, Margaret L Kern, Lukasz Dziurzynski, Stephanie M Ramones, Megha Agrawal, Achal Shah, Michal Kosinski, David Stillwell, Martin EP Seligman, et al. 2013 · 2013
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Quantifying mental health signals in Twitter
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Developing age and gender predictive lexica over social media
Predicting responses to psychological questionnaires from participants’ social media posts and question text embeddings
Huy Vu, Suhaib Abdurahman, Sudeep Bhatia, and Lyle Ungar. 2020 · 2020
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Team phoenix at WASSA 2021: Emotion analysis on news stories with pre-trained language models
Yash Butala, Kanishk Singh, Adarsh Kumar, and Shrey Shrivastava. 2021 · 2021
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MeLT: Message-level transformer with masked document representations as pre-training for stance detection
Matthew Matero, Nikita Soni, Niranjan Balasubramanian, and H. Andrew Schwartz. 2021 · 2021
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Empirical evaluation of pre-trained transformers for human-level NLP: The role of sample size and dimensionality
Adithya V Ganesan, Matthew Matero, Aravind Reddy Ravula, Huy Vu, and H. Andrew Schwartz. 2021 · 2021
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Learning to answer psychological questionnaire for personality detection
Feifan Yang, Tao Yang, Xiaojun Quan, and Qinliang Su. 2021b · 2021
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Maarten Sap, Gregory Park, Johannes Eichstaedt, Margaret Kern, David Stillwell, Michal Kosinski, Lyle Ungar, and Hansen Andrew Schwartz. 2014 · 2014
Cited alongside, same era.
Automatic personality assessment through social media language
Gregory Park, H. A. Schwartz, J. Eichstaedt, M. Kern, M. Kosinski, D. Stillwell, Lyle H. Ungar, and M. Seligman. 2015 · 2015
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The role of the five-factor model in personality assessment and treatment planning
R Michael Bagby, Tara M Gralnick, Nadia Al-Dajani, and Amanda A Uliaszek. 2016 · 2016
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Detecting depression and mental illness on social media: an integrative review
Sharath Chandra Guntuku, David Bryce Yaden, Margaret L. Kern, Lyle H. Ungar, and Johannes C. Eichstaedt. 2017 · 2017
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Latent human traits in the language of social media: An open-vocabulary approach
Vivek Kulkarni, Margaret L. Kern, David Stillwell, Michal Kosinski, Sandra C. Matz, Lyle H. Ungar, Steven Skiena, and H. A. Schwartz. 2017 · 2017
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Facebook language predicts depression in medical records
Johannes C Eichstaedt, Robert J Smith, Raina M Merchant, Lyle H Ungar, Patrick Crutchley, Daniel Preoţiuc-Pietro, David A Asch, and H Andrew Schwartz. 2018 · 2018
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User-level race and ethnicity predictors from twitter text
Daniel Preotiuc-Pietro and Lyle H. Ungar. 2018 · 2018
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Using paraphrases to study properties of contextual embeddings
Laura Burdick, Jonathan K. Kummerfeld, and Rada Mihalcea. 2022 · 2022
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Palm: Scaling language modeling with pathways
Aakanksha Chowdhery, Sharan Narang, Jacob Devlin, Maarten Bosma, Gaurav Mishra, Adam Roberts, Paul Barham, Hyung Won Chung, Charles Sutton, Sebastian Gehrmann, et al. 2022 · 2022
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Using facebook language to predict and describe excessive alcohol use
R Jose, M Matero, G Sherman, B Curtis, S Giorgi, HA Schwartz, and LH Ungar. 2022 · 2022
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Pushing on personality detection from verbal behavior: A transformer meets text contours of psycholinguistic features
Elma Kerz, Yu Qiao, Sourabh Zanwar, and Daniel Wiechmann. 2022 · 2022
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Using commonsense knowledge to answer why-questions
Yash Kumar Lal, Niket Tandon, Tanvi Aggarwal, Horace Liu, Nathanael Chambers, Raymond Mooney, and Niranjan Balasubramanian. 2022 · 2022
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Evaluating contextual embeddings and their extraction layers for depression assessment
Matthew Matero, Albert Hung, and H. Andrew Schwartz. 2022 · 2022
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Language models are multilingual chain-of-thought reasoners
Freda Shi, Mirac Suzgun, Markus Freitag, Xuezhi Wang, Suraj Srivats, Soroush Vosoughi, Hyung Won Chung, Yi Tay, Sebastian Ruder, Denny Zhou, et al. 2022 · 2022
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Challenging big-bench tasks and whether chain-of-thought can solve them
Mirac Suzgun, Nathan Scales, Nathanael Scharli, Sebastian Gehrmann, Yi Tay, Hyung Won Chung, Aakanksha Chowdhery, Quoc V. Le, Ed Huai hsin Chi, Denny Zhou, and Jason Wei. 2022 · 2022
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WWBP-SQT-lite: Multi-level models and difference embeddings for moments of change identification in mental health forums
Adithya V Ganesan, Vasudha Varadarajan, Juhi Mittal, Shashanka Subrahmanya, Matthew Matero, Nikita Soni, Sharath Chandra Guntuku, Johannes Eichstaedt, and H. Andrew Schwartz. 2022 · 2022
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Psychology
American Psychological Association APA. 2023 · 2023
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Gpt as knowledge worker: A zero-shot evaluation of (ai) cpa capabilities
Jillian Bommarito, Michael Bommarito, Daniel Martin Katz, and Jessica Katz. 2023 · 2023
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