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’m also interested in developing methods to quantify social interaction, promoting open science research and education, and creating opportunities for cognitive scientists and psychologists who are interested in big data, naturally occurring data, and data science, with a special focus on data ethics.
I’m actively recruiting lab members, so please send me your CV and a brief description of your research interests if you’d like to be considered!
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; and the Connecticut Institute for the Brain and Cognitive Sciences.
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
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. Check out my contribution to the Psychonomic Society's #PSBigData Digital Event, in honor of the new special issue of Behavior Research Methods! (And don't forget to check out Dennis et al.'s (2019) exciting 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, forthcoming, Studies in Perception and Action XV: Proceedings from the Twentieth International Conference on Perception and Action). Read our preprint!
Grant: Along with PI R. Stuart Geiger (University of California, Berkeley) and fellow co-PI Lilly Irani (Lilly Irani, University of California, San Diego), our team won an interdisciplinary grant from the Ford and Ford Foundations to help our understanding of important digital infrastructure. Check out the announcement from Ford!
Methods development: Automatically and reproducibly quantify multi-level linguistic alignment in natural conversation with ALIGN (Duran, Paxton, & Fusaroli, accepted, Psychological Methods). Find our Python package on GitHub, or install it directly from PyPI. Read about it in our preprint on PsyArXiv!
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).
Outreach: Videos and code from the Data on the Mind 2017 summer workshop are now available! Check out 11 tutorials dedicated to helping cognitive scientists explore questions about cognition and behavior with big and naturally occurring data. Find out more through the links below.