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Ryan Boyd

Ryan Boyd

Assistant Professor - Department of Psychology

Language is everywhere — it gives shape to our thoughts and experiences, helping us navigate the world. I use computational methods (natural language processing, machine learning, etc.) to study how language provides clues about how we think, feel, and act in everyday life.

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Professional Preparation

Ph.D. - Social/Personality Psychology
University of Texas at Austin - 2017
M.Sc. - Social/Health Psychology
North Dakota State University - 2012
B.A. - Psychology
Purdue University Ft. Wayne - 2010

Research Areas

Brief Profile
Dr. Ryan L. Boyd is an Assistant Professor of Psychology at the University of Texas at Dallas. He studies how everyday language reflects and shapes human psychology — from personality and emotion to social connection and mental health — in both laboratory and real-world settings. His cross-disciplinary work spans psychology, computational social science, and NLP, and includes large-scale studies of natural text, validated language measures, and collaborations that translate findings into practical tools and interventions. He has authored 100+ scholarly papers and co-edited The Handbook of Language Analysis in Psychology. Boyd is a leading contributor to the Linguistic Inquiry and Word Count (LIWC) project and has developed numerous open-source text-analysis applications used by researchers and practitioners. His work has been cited by policy and regulatory bodies, including the U.S. National Security Commission on Artificial Intelligence and the European Commission’s Joint Research Centre, and he serves on editorial and advisory boards across psychology and computational social science.

Publications

Entwistle, C., Hoemann, K., Nightingale, S. J., & Boyd, R. L. (2025). Psychosocial dynamics of suicidality and nonsuicidal self-injury: A digital linguistic perspective. npj Mental Health Research, 4(28), 1–13. https://doi.org/10.1038/s44184-025-00142-w
2025 - publications
Oosthuizen, I., Swanepoel, D. W., Boyd, R. L., Pennebaker, J. W., Launer, S., & Manchaiah, V. (2025). Exploring adult hearing aid user experiences: Meaning extraction methods, content patterns, and associations with demographic and outcome variables. International Journal of Audiology, 64(9), 909–919. https://doi.org/10.1080/14992027.2024.2415958 2025 - publications
Mangalik, S., V Ganesan, A., Wheeler, A. B., Kerry, N., Clifton, J. D. W., Schwartz, H., & Boyd, R. L. (2025). Capturing author self beliefs in social media language. In W. Che, J. Nabende, E. Shutova, & M. T. Pilehvar (Eds.), Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) (pp. 1362–1376). Association for Computational Linguistics. https://aclanthology.org/2025.acl-long.69/ 2025 - publications
Rao, R., V Ganesan, A., Kjell, O., Luby, J., Raghavan, A., Feltman, S. M., Ringwald, W., Boyd, R. L., Luft, B. J., Ruggero, C. J., Ryant, N., Kotov, R., & Schwartz, H. (2025). WhiSPA: Semantically and psychologically aligned Whisper with self-supervised contrastive and student-teacher learning. In W. Che, J. Nabende, E. Shutova, & M. T. Pilehvar (Eds.), Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) (pp. 22529–22544). Association for Computational Linguistics. https://aclanthology.org/2025.acl-long.1098/ 2025 - publications
Singh, K., Varadarajan, V., V Ganesan, A., Nilsson, A. H., Soni, N., Mahwish, S., Chitale, P., Boyd, R. L., Ungar, L., Rosenthal, R. N., & Schwartz, H. (2025). Systematic evaluation of auto-encoding and large language model representations for capturing author states and traits. In W. Che, J. Nabende, E. Shutova, & M. T. Pilehvar (Eds.), Findings of the Association for Computational Linguistics: ACL 2025 (pp. 18955–18973). Association for Computational Linguistics. https://aclanthology.org/2025.findings-acl.971/ 2025 - publications
Collins, K. A., & Boyd, R. L. (2025). Automating the detection of linguistic intergroup bias through computerized language analysis. Journal of Language and Social Psychology, 44(3–4), 343–366. https://doi.org/10.1177/0261927X251318887  2025 - publications
Fetterman, A. K., Evans, N. D., Ravey, E. P., Henderson, P. R., Tran, B. H. L., & Boyd, R. L. (2025). The topics of nostalgic recall: The benefits of nostalgia depend on the topics that one recalls. Social Psychological and Personality Science, 16(4), 444–456. https://doi.org/10.1177/19485506241229305 2025 - publications
Lahnala, A., Varadarajan, V., Flek, L., Schwartz, H. A., & Boyd, R. L. (2025). Unifying the extremes: Developing a unified model for detecting and predicting extremist traits and radicalization. Proceedings of the International AAAI Conference on Web and Social Media, 19, 1051–1067. https://doi.org/10.1609/icwsm.v19i1.35860
2025 - publications

Appointments

Assistant Professor of Psychology
Department of Psychology, University of Texas at Dallas [2024–Present]
Affiliated Faculty
Texas Artificial Intelligence Research Institute, University of Texas at Dallas [2025–Present]
https://tairi.utdallas.edu/
Associate Research Professor / Principal Research Scientist
Department of Computer Science, Stony Brook University [2023–2024]
Computational Social Scientist
Behavioral Science Lab & Threat Research Lab, ByteDance / TikTok [2022–2023]
Assistant Professor of Behavioral Analytics
Department of Psychology / Data Science Institute / Security Lancaster, Lancaster University [2019–2022]
Visiting Scholar
Adaptive Systems and Interaction Research Group, Microsoft Research [2018–2018]
Visiting Scholar
HLAB, Department of Computer Science, Stony Brook University [2018–2018]
Postdoctoral Fellow
Department of Psychology, University of Texas at Austin [2017–2019]

News Articles

How Online Language Choices May Signal Self-Harm Risk
AI, Computers and Humans: the Social Implications | Perspectives Matter
Forbes — Using Generative AI To Figure Out What People Mean Versus What They Say
PBS — How language nerds solve crimes
California Management Review — Computers as Creative Collaborators for Businesses?

Funding

Digital Interventions to Mitigate Behavioral Health Access Barriers in North Texas
400,000 - Texas Higher Education Coordinating Board (THECB) Minority Health Grant Program (MHGP) []
Co-Investigator
Enhancing Large Language Models for Cognitive Behavioral Therapy Conversations
$25,000 - University of Texas at Dallas NFRS Seed Program [2025/08–2025/07]
Co-Principal Investigator
Centre for Research and Evidence on Security Threats (CREST)
$7,300,000 - Economic and Social Research Council (ESRC ES/V002775/1) [2020/07–2022/06]
Co-Investigator
News media and shared representations: The development and validation of an automated approach to the detection of linguistic bias
$52,000 - Social Sciences and Humanities Research Council, Insight Development Grant (SSHRC-IDG 430-2020-00212) [2020/06–2023/06]
Collaborating Investigator
Computational social science: Social data bias
$183,687 - Alan Turing Institute, UK Defence Science and Technology Laboratory [2021/06–2022/05]
Co-Investigator