Data-rich human communication

As a cognitive scientist and data scientist, I take a data-rich approach to understanding how people collaborate, bond, and fight. To do that, I weave together a variety of data sources from the lab and the real world for a converging tapestry of the many ways in which our language, movement, decisions, and emotions change during social contact. Understanding how context—including conversational goals, social connections, and physical spaces—shape our emerging behaviors is a primary goal of my research, embedded within rich traditions of dynamical and ecological perspectives on human behavior and cognition broadly.

I also develop methods to quantify social interaction, promote open science research and education, and create opportunities for cognitive scientists and psychologists who are interested in data science, naturally occurring data, and big data, with a special focus on data ethics. Advocating for diversity, equity, and inclusion is an essential part of my scholarly, mentoring, and pedagogical work.

About me

I’m an assistant professor in the University of Connecticut’s Department of Psychological Sciences, specifically within the Perception, Action, Cognition division. I am affiliated with the Center for the Ecological Study of Perception and Action; the Institute for Collaboration on Health, Intervention, and Policy; the Connecticut Institute for the Brain and Cognitive Sciences; and the Cognitive Science program. I am also a faculty mentor in the Science of Learning and Art of Communication training program.

I’m proud to lead the dyscord lab. Together, we explore the dynamics of social communication and inter-organism dependencies. Our lab includes several graduate students — Megan Chiovaro, Lana Delasanta, Caitrín (“Cat”) Hall, and Gray Thomas (starting in Fall 2021) — and a number of bright and hard-working current and former undergraduate research assistants. You can find out more about our community and our work at our lab website. (If you’re an undergraduate student interested in working with the lab, please fill out this form.)

Previously, I was a postdoctoral scholar working with Tom Griffiths in the Institute of Cognitive and Brain Sciences at the University of California, Berkeley and a Moore-Sloan Data Science Fellow at the Berkeley Institute for Data Science. I received my Ph.D in Cognitive and Information Sciences working with Rick Dale at the University of California, Merced.

Some recent work

Publication: Graduate student Lena Müller-Frommeyer (TU Braunschweig) won a prestigious grant to join me at UConn in my lab last summer, and together with her thesis advisor Simone Kauffeld (TU Braunschweig), we put together an exciting paper on the context-dependency of individual language style. It was recently published in Cognitive Science. Check out the open-access publication, code, and data at the links below!

Invited blog post: Psychological scientists can do big data research while preserving our ethical responsibilities to our participants and our commitments to improving the openness and transparency of science. My contribution to the Psychonomic Society's #PSBigData Digital Event---in honor of the new special issue of Behavior Research Methods---focuses on some exciting new solutions and big open questions. (And don't forget to check out Dennis et al.'s (2019) great open-access piece on privacy and open science for researchers doing large-scale data collection.)

Conference proceedings: We argue that ecological psychology must grow to consider how intersectionality (Crenshaw, 1991) impacts social effectivities and social affordances (Paxton, Blau, & Weston, 2019, Studies in Perception and Action XV: Proceedings from the Twentieth International Conference on Perception and Action).

Methods development: Automatically and reproducibly quantify multi-level linguistic alignment in natural conversation with ALIGN (Duran, Paxton, & Fusaroli, 2019, Psychological Methods). Find our Python package on GitHub, or install it directly from PyPI!

Improving public policy: Open science can be transformative to data-intensive psychology and cognitive science, and US policy makers can help foster the adoption of open-science policies (Paxton & Tullett, 2019, Policy Insights from the Behavioral and Brain Sciences).