Teaching

NETS 1120: Networked Life

How do infectious diseases spread? Why do some memes spread virally while others do not? Why do some teams or organizations perform better than others? Are we all really connected by six degrees of separation and, if so, how is that are our neighborhoods, workplaces, and social circles are so segregated? The answers to these questions and many more are all part of Network Science, a fascinating subject at the intersection of many disciplines, including computer science, communications, psychology, sociology, mathematics, and economics. This course will provide an introduction to the technical language of network science as well as to a collection of applications such as mathematical epidemiology, social contagion, games of cooperation and coordination, and collective problem solving.

Date: Fall 2022

TR 10:15am-11:44am (8/30 to 12/12) 

Course type: Lecture

 

OIDD 953/CIS 798/COMM 898: Explaining Explanation

In the social sciences we often use the word “explanation” as if (a) we know what we mean by it, and (b) we mean the same thing that other people do. In this course we will critically examine these assumptions and their consequences for scientific progress. In part 1 of the course we will examine how, in practice, researchers invoke at least three logically and conceptually distinct meanings of “explanation:” identification of causal mechanisms; ability to predict (account for variance in) some outcome; and ability to make subjective sense of something. In part 2 we will examine how and when these different meanings are invoked across a variety of domains, focusing on social science, history, business, and machine learning, and will explore how conflation of these distinct concepts may have created confusion about the goals of science and how we evaluate its progress. Finally, in part 3 we will discuss some related topics such as null hypothesis testing and the replication crisis. We will also discuss specific practices that could help researchers clarify exactly what they mean when they claim to have “explained” something, and how adoption of such practices may help social science be more useful and relevant to society.

Date: Spring 2022

Course type: PhD seminar

Teaching

NETS 1120: Networked Life

How do infectious diseases spread? Why do some memes spread virally while others do not? Why do some teams or organizations perform better than others? Are we all really connected by six degrees of separation and, if so, how is that are our neighborhoods, workplaces, and social circles are so segregated? The answers to these questions and many more are all part of Network Science, a fascinating subject at the intersection of many disciplines, including computer science, communications, psychology, sociology, mathematics, and economics. This course will provide an introduction to the technical language of network science as well as to a collection of applications such as mathematical epidemiology, social contagion, games of cooperation and coordination, and collective problem solving.

Date: Fall 2022

TR 10:15am-11:44am (8/30 to 12/12)

Course type: Lecture

OIDD 953/CIS 798/COMM 898: Explaining Explanation

In the social sciences we often use the word “explanation” as if (a) we know what we mean by it, and (b) we mean the same thing that other people do. In this course we will critically examine these assumptions and their consequences for scientific progress. In part 1 of the course we will examine how, in practice, researchers invoke at least three logically and conceptually distinct meanings of “explanation:” identification of causal mechanisms; ability to predict (account for variance in) some outcome; and ability to make subjective sense of something. In part 2 we will examine how and when these different meanings are invoked across a variety of domains, focusing on social science, history, business, and machine learning, and will explore how conflation of these distinct concepts may have created confusion about the goals of science and how we evaluate its progress. Finally, in part 3 we will discuss some related topics such as null hypothesis testing and the replication crisis. We will also discuss specific practices that could help researchers clarify exactly what they mean when they claim to have “explained” something, and how adoption of such practices may help social science be more useful and relevant to society.

Date: Spring 2022

Course type: PhD seminar