Active Projects

Understanding the Dynamics of Supportive Conversations

This project examines the interpersonal dynamics in supportive conversations and how certain dynamics help support receivers.

Using supportive conversations observed in the lab, we are describing the turn-by-turn dynamics of these interactions as well as developing methods to better understand these dynamics.

Specific work:

  • Examines the types of turns that comprise supportive conversations

  • Proposes studying supportive interactions using a dynamic systems approach

  • Provides tutorials for implementing the methods we use

The Texting Life of Couples Study

The Texting Life of Couples (TLC) Study examines how new romantic couples text in their daily lives.

Using text message logs from new romantic couples, we are able to examine when and what couples text each other over the course of their relationship.

Specific work examines:

  • How texting behaviors, such as frequency, responsiveness, and message length, change during relationship development

  • How couples' language use becomes more similar over time

  • How couples' frequency of texting is associated with different personal (e.g., attachment style) and relational characteristics (e.g., relationship satisfaction)


The Human Screenome Project uses new screen capture methodology to understand digital life.

The project team has a wide range of goals from studying how people multitask to where people get their news.

Specific work I'm involved with examines:

  • How the time spent on screen content differs by the type of content

  • How individuals idiosyncratically move through textual and graphical content on their devices

Check out The Screenomics Lab webpage to learn more!

Developing Methods to Study Interpersonal Interactions

Across different projects, sometimes new methods need to be developed to address our research questions.

To better describe and model interaction dynamics, my colleagues and I have:

  • Developed grid-sequence analysis, a method that summarizes dyad-level dynamics using a combination of state space grids (used in developmental psychology) and sequence analysis (a technique drawn from molecular biology)

  • Extended the one-with-many model to accommodate repeated measures and examine features of multiple dyadic relationships that one set of focal persons (e.g., therapists, social media users) has with others (e.g., multiple clients, friends on social media)