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Ryan Boyd

Ryan Boyd

Assistant Professor

Research Interests: Computational social science, verbal behavior, personality and individual differences, social interaction, mental health, natural language processing, text analysis, machine learning, AI in psychology

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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

Language is everywhere — we use language to understand and shape to our thoughts and experiences, influence the behavior of others, and engage in the social universe that binds us together. My research uses computational social science methods (natural language processing, machine learning, etc.) to understand how our language provides clues about how we think, feel, and behave. I have several active programs of research spanning topics ranging from the language of personality to society, mental health, human sexuality, and storytelling. Most of my research involves the use of the words that people use in everyday life (conversations, social media, personal writing, etc.) to study the psychology of personality, social interaction, and emotions.

Publications

Varadarajan, V., Lahnala, A., Ganesan, A. V., Dey, G., Mangalik, S., Bucur, A.-M., Soni, N., Rao, R., Lanning, K., Vallejo, I., Flek, L., Schwartz, H. A., Welch, C., & Boyd, R. L. (2024). Archetypes and entropy: Theory-driven extraction of evidence for suicide risk. In A. Yates, B. Desmet, E. Prud’hommeaux, A. Zirikly, S. Bedrick, S. MacAvaney, K. Bar, M. Ireland, & Y. Ophir (Eds.), Proceedings of the 9th Workshop on Computational Linguistics and Clinical Psychology (CLPsych 2024) (pp. 278–291). Association for Computational Linguistics. https://aclanthology.org/2024.clpsych-1.28 2024 - publications
Ganesan, A. V., Mangalik, S., Varadarajan, V., Soni, N., Juhng, S., Sedoc, J., Schwartz, H. A., Giorgi, S., & Boyd, R. L. (2024). From text to context: Contextualizing language with humans, groups, and communities for socially aware NLP. In R. Zhang, N. Schneider, & S. Chaturvedi (Eds.), Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 5: Tutorial Abstracts) (pp. 26–33). Association for Computational Linguistics. https://aclanthology.org/2024.naacl-tutorials.4 2024 - publications
Markowitz, D. M., Boyd, R. L., & Blackburn, K. (2024). From silicon to solutions: AI’s impending impact on research and discovery. Frontiers in Social Psychology: Computational Social Science, 2, 1–14. https://doi.org/10.3389/frsps.2024.1392128 2024 - publications
Dworakowski, O., Meier, T., Mehl, M. R., Pennebaker, J. W., Boyd, R. L., & Horn, A. B. (2024). Comparing the language style of heads of state in the US, UK, Germany and Switzerland during COVID-19. Scientific Reports, 14(1), 1708. https://doi.org/10.1038/s41598-024-51362-7 2024 - publications
Stanton, A. M., Boyd, R. L., O’Cleirigh, C., Olivier, S., Dolotina, B., Gunda, R., Koole, O., Gareta, D., Modise, T. H., Reynolds, Z., Khoza, T., Herbst, K., Ndung’u, T., Hanekom, W. A., Wong, E. B., Pillay, D., Siedner, M. J., & Team,  for the V. S. (2024). HIV, multimorbidity, and health-related quality of life in rural KwaZulu-Natal, South Africa: A population-based study. PLOS ONE, 19(2), e0293963. https://doi.org/10.1371/journal.pone.0293963 2024 - publications
Date, S., Deshmukh, S. N., Boyd, R., Ashokkumar, A., & Pennebaker, J. W. (2024). Designing of a novel framework for Marathi natural language processing: MR-LIWC2015. International Journal of Intelligent Systems and Applications in Engineering, 12(11s), 1–14. Retrieved from https://www.ijisae.org/index.php/IJISAE/article/view/4414 2024 - publications
Boyd, R. L., & Markowitz, D. M. (in press). Verbal behavior and the future of social science. American Psychologisthttps://doi.org/10.1037/amp0001319 2024 - publications
Mihalcea, R., Biester, L., Boyd, R. L., Jin, Z., Pérez-Rosas, V., Wilson, S., & Pennebaker, J. W. (in press). How developments in natural language processing help us understand human behavior. Nature Human Behaviour. 2024 - publications

Appointments

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

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?
PsyPost — Verbal cues of authenticity are linked to positive social and business outcomes, according to new research
Planet Word — Putin, Bush, and Pronouns: Presaging War?

Funding

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]
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]
Computational social science: Social data bias
$183,687 - Alan Turing Institute, UK Defence Science and Technology Laboratory [2021/06–2022/05]
The language of the COVID-19 pandemic: Investigating official communication and its relations with collective and individual emotions
$192,800 - Swiss National Science Foundation (Project ID: #196255) [2020/06–2022/05]
Arc of Narrative Method (AON) used to advance strategies used in intelligence interviewing and interrogation
$840,104 - Federal Bureau of Investigation (DJF-15F06718C0002523) [2018/06–2020/05]