When social psychologists want to know what people think and do, they ask questions. Unfortunately, the answers can be shaped by subtle details of the research instrument and context in ways the researcher never intended. This workshop addresses the cognitive and communicative processes involved in asking and answering questions in research situations.  It provides an introduction to the following themes: How do people make sense of the questions we ask? How can we assess meaningful reports of behavior, feelings, and evaluations? What are the implications the ubiquitous context sensitivity of the reports? What can we do about it? That’s an ambitious program for a day and it requires that all participants read some papers in advance. The readings will be distributed after sign-up; for an overview of these themes, follow this link to a 2012 chapter pdf.

Instructor: Arthur Stone

Big Data:

In the past several years, social scientists have been facing a quantitative change in technology. This change can be summarized in two main points: 1. availability of vast and seemingly insurmountable volumes of human-related data, and 2. constantly increasing computational power. These have provided an unprecedented opportunity to study and model human cognition with range and detail previously not imaginable. Moreover, there is growing interest to use such data for predicting a variety of human behavior, for detecting different types of activities, or for more intelligent targeted advertising. The focus of this workshop is on machine learning methods that can help us achieve these outcomes. We will specifically focus on the following topics: Classification, Resampling, Model Selection, Tree-Based Methods, Support Vector Machines and several Unsupervised Learning methods. In addition to covering these topics, we will also provide hands-on R training for applying methods for data analysis.

Instructor: Morteza Dehghani