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Livestream Seminar

Social Networks: Statistical Approaches

A 3-Day Livestream Seminar Taught by

John Skvoretz
Course Dates:

Thursday, November 10 –
Saturday, November 12, 2022

Schedule: All sessions are held live via Zoom.

10:00am-12:30pm ET (New York time)
1:30pm-4:00pm ET Thursday, 1:30pm-3:30pm ET Friday & Saturday

The study of social networks focuses on relationships among the units of some population, and on how the structure of these ties affects outcomes experienced by both the units and the population. Often the units are persons or individuals, but they may be families, households, corporations, or nation states.

Social network analysis is a set of methods for describing, quantifying and analyzing the properties of social networks. This seminar is a survey of statistical methods for analyzing social network data. It will focus on testing hypotheses about:

    • network structure (e.g. reciprocity, transitivity, centralization),
    • the formation/dissolution of ties based on attributes (e.g. homophily),
    • local structural effects.

Starting November 10, we are offering this seminar as a 3-day synchronous*, livestream workshop held via the free video-conferencing software Zoom. Each day will consist of two lecture sessions which include hands-on exercises, separated by a 1-hour break. Participants are encouraged to join the lecture live, but will have the opportunity to view the recorded session later in the day if they are unable to attend at the scheduled time.

*We understand that scheduling is difficult during this unpredictable time. If you prefer, you may take all or part of the course asynchronously. The video recordings will be made available within 24 hours of each session and will be accessible for four weeks after the seminar, meaning that you will get all of the class content and discussions even if you cannot participate synchronously. 

Closed captioning is available for all live and recorded sessions.

More details about the course content


Who should register?

Seminar outline

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“My favorite part of this seminar was walking through examples in R in real time."

“My favorite part of this seminar was walking through examples in R in real time. This allowed me to follow along, and write comments in the provided scripts that interpreted the commands and output.” 

Nicole Johnson

Temple University 

"... very knowledgeable and provided relevant materials and interactive sessions..."

“As a grad student working full time, this survey course on social network statistical approaches was an excellent opportunity to learn, and improve my understanding of, some very useful social network statistical tools. The instructor was excellent – very knowledgeable and provided relevant materials and interactive sessions that helped me with questions I had about using social network statistics in my dissertation research. Highly recommended!”

Nelson Jatel

Roads University

"John understands every detail of complex network models..."

“This course was really helpful because I had access to real R scripts that I can use and replicate for my own research. John understands every detail of complex network models and explains them in a very clear way.”

Seungho (Andy) Back

University of Toronto

“I thought this was a fantastic course..."

“I thought this was a fantastic course. This course helped to clarify and expand upon what I had previously learned. Learning how to test if certain network structures are significantly different from chance was useful and getting a detailed explanation of how to interpret ERGM terms and ERGM model fit statistics was much better through this course than what I’ve previously tried to teach myself with textbooks.”

Megan Evans

Pennsylvania State University

“The material is very relevant to audiences outside of its origins..."

“The material is very relevant to audiences outside of its origins in sociology and related fields. It demonstrates the presence of mathematical rigor in an aspect of studying relationships that allows researchers to go beyond descriptive statistics and pretty pictures.”

Steve Vejcik