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.

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’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.

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

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.

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, in press, Policy Insights from the Behavioral and Brain Sciences). Read our preprint here!

Conference proceedings: Explore the emergence of perceptual and memory coordination during minimally interactive (online) contexts (Paxton, Morgan, Suchow, & Griffiths, 2018, Proceedings of the Cognitive Science Society). Read our proceedings paper, and check out the code for our experiment and analyses on our GitHub repository!

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

Call to action: Use big or naturally occurring data sets (BONDS) to test theories outside the lab by finding the traces of the behavioral and cognitive processes within the human-generated data (Paxton & Griffiths, 2017, Behavior Research Methods). Read the open-access article!