Psychology 241: Models of Social Behavior
Tuesdays and Thursdays, 2:15 - 4:05
How do we reason about other people and ourselves? Is human behavior in social situations a set of ad-hoc and irrational responses – or can we understand humans as making rational inferences under uncertainty about the people they are interacting with? This project-based seminar will re-examine classic findings from social psychology and affective science through the lens of rational analysis and probabilistic models. In collaboration with instructors, students will develop projects focused on making testable theoretical models of classic tasks and literatures with the goal of creating a publishable end product. Phenomena under consideration include but are not limited to: cognitive dissonance, attribution theory, mindset theory, stereotyping, and emotion perception.
Students are strongly encouraged to first take Psych 204 (on probabilistic models). For undergraduates wishing to participate this course is a required pre-requisite, except by special permission of the instructors.
The goal of this class will be a piece of original research from each group, suitable for presentation at a major conference such as CogSci or SPSP.
We will assemble 4 - 6 groups during the 2nd week of class. Students will fill out a questionnaire ranking their interests in our suggested project topics, as well as their background in modeling and social psychology / affective science. Suggested topics are as follows:
Project milestones / assignments
Students will take their project through 4 major milestones, one in each ~2 week period of the quarter. Each will be associated with a graded assignment as follows:
Weeks 1 - 3 will be an intensive introductory short course described here, while later weeks will feature discussions on targeted project areas, led by individual student groups. Weeks 4-10 will comprise students’ presentations of various stages of their project, culminating in a final presentation open to all members of the psychology department on the last day of class (6/3).
Week 1 - Bayesian modeling of lay theories (Noah)
Bayesian models have been used very effectively to capture people’s knowledge and commonsense reasoning: intuitive theories about the world. The key thread that connects this tradition to the affective and social realm is the central roles of lay theories. This course is about Bayesian models of lay theories.
04/01. Modeling lay theories.
Before class: work through primer on scheme syntax (probmods.org Chapter 12)
Reading: probmods.org, Chapters 1 and 2
04/03. Theories about people.
Before class: do exercises 1 and 2 of Chapter 1, and exercise 3 of Chapter 2.
Week 2 - Fitting models to data (Mike)
During this week we will discuss why we make models and how to connect models to data. We’ll focus on discussing the practical and theoretical issues underlying making the claim that a model provides a formal theory for a particular domain or phenomenon.
04/08. Why model?
Before class: fill out this form about project topics
04/10. Case studies of model evaluation
Before class: find a published graph comparing a model to empirical data and send it to Mike. Prize for the best one.
Week 3 - Lay theories: the phenomena (Jamil)
During this week, we will leverage what we have learned about modeling more generally to consider classic topics from social psychology through a new lens. We will begin with inferences about others, and move (on Thurs) to inferences individuals make about themselves.
04/15. Theories about the self
Additional supplemental reading: Funder, 1987
Inspiration for modeling: application of Bayesian techniques to learned helplessness.
04/17. Theories about other people
Week 4: Student Presentations
04/22. Background: Groups 1 & 2
04/24. Background: Groups 3 & 4
Week 5: Student Presentations
04/29. Operationalization 1: Groups 1 & 2
05/01. Operationalization 1: Groups 1 & 2
Week 6: Student Presentations
05/06. Models round 1: Groups 1 & 2
05/08. Models round 1: Groups 3 & 4
Week 7: Student Presentations
05/13. Models round 2: Groups 1 & 2
05/15. Models round 2: Groups 3 & 4
Week 8: Student Presentations
05/20. Data / simulations round 1: Groups 1 & 2
05/22. Data / simulations round 1: Groups 1 & 2
Week 9: Student Presentations
05/27. Data / simulations round 2: Groups 1 & 2
05/29. Data / simulations round 2: Groups 1 & 2
Week 10: Final Presentations
06/03. Final Presentations: Groups 1-6