Social Networks

What does our digital footprint say about us?

Carillon students at prototype day In this digital world most of our daily activities leave a large digital footprint that is being used to infer about our hobbies, our state of being, and our political and social views. It is important that we educate ourselves on how that data is being gathered, what it is being used for, and why it can be both a blessing and a curse.

You can expect to:

  • Collect, organize, and analyze publicly available social network data.
  • Learn basic graph theory concepts and their use in the analysis of social network data.
  • Work in small teams on open-ended projects involving social network data.

*This community is targeted to non-mathematics and non-computer science majors.

Community Course

MATH270 - Social Networks: A Mathematical Exploration. Learn how to use basic mathematical concepts, especially graph theory, to gain a good understanding of social networks. Use simple computer softwares to visualize and analyze graphs corresponding to social networks. (3 credit course, fulfills General Education requirements of I-Series and Scholarship in Practice)
View the Fall 2019 draft syllabus for MATH270.

Instructor

Picture of Kasso OkoudjouProfessor Kasso Okoudjou is a Professor in the Department of Mathematics who joined the University in 2006. Okoudjou is interested in broadening the participation of underrepresented undergraduate students in research in the mathematical sciences. He is member of UMD’s SEMINAL team (Student Engagement in Mathematics Through an Institutional Network of Active Learning), working on introducing active learning in precalculus and calculus courses. Okoudjou’s research interests include applied, computational, and pure harmonic analysis, as well as analysis on graphs and fractals. Professor Okoudjou held visiting positions at the University of Osnabruck, the Technical University of Berlin, the Mathematical Sciences Research Institute, and MIT. Okoudjou was awarded the 2009 Dean's Award for Excellence in Teaching for the College of Computer, Math and Physical Sciences.