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Livestream Seminar

Introduction to Social Network Analysis

A 3-Day Livestream Seminar Taught by

Filip Agneessens
Course Dates: Ask about upcoming dates
Schedule:

10:00am-1:00pm ET (New York time): Live session via Zoom
2:30pm-4:30pm ET: Live session via Zoom

Interest in social networks has been climbing exponentially since the 1970s. For social scientists, networks can be seen as a fundamental adaptation that facilitates the coordination and distribution of resources, while simultaneously maintaining the flexibility of independent agents. For physical scientists, networks can be seen as universal structures underlying everything from molecules to galaxies. And for mathematicians and computer scientists, networks provide an abstract and propitious way of representing problems.

The field of social network analysis consists of a vocabulary of theoretical and mathematical concepts for investigating network phenomena, along with a distinctive data model and set of methodologies for collecting and analyzing network data. This course provides an overview of the core concepts and methods in social network analysis.

Starting April 28, 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 2 lecture sessions which include hands-on exercises, separated by a 1.5-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

Computing

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