a random graph showing points scattered around and connected by red lines and blue lines

Contagion

Graph by Nicole Eikmeier, published in "Coin-Flipping, Ball-Dropping, and Grass-Hopping for Generating Random Graphs from Matrices of Edge Probabilities," SIAM Rev., 61(3), 549–595.

Contagion

A First-Year Tutorial offered fall 2021, taught by Nicole Eikmeier, assistant professor of computer science

In a global pandemic, how does a virus spread across the world? In the information age, how does “fake news” turn into wide-believed facts? How do social justice movements such as #BlackLivesMatter and #MeToo take hold? Each of these questions can be answered with networks: relationships of people and things. This tutorial will explore how various things (diseases or ideas) spread, through the lens of network science. We will study classical ideas of network science through modern applications, to better understand the world around us. This tutorial will have an analytical component.

Nicole Eikmeier

Why I’m Teaching This Topic

I enjoy thinking about networks because they allow us to understand many phenomena of human interaction. Network science has lots of disciplinary interests as well – I'm interested in the math behind networks; others are interested in epidemiological applications (such as the spread of disease) or social applications (how humans interact with each other). It's a topic that can be accessed from many different angles and will push students to rethink the world around them. 

– Nicole Eikmeier

We use cookies to enable essential services and functionality on our site, enhance your user experience, provide better service through personalized content, collect data on how visitors interact with our site, and enable advertising services.

To accept the use of cookies and continue on to the site, click "I Agree." For more information about our use of cookies and how to opt out, please refer to our website privacy policy.