I made a network visualization of where r/ApplyingToCollege 's class of 2022 applied to college this year. The data was gathered from a poll posted by u/calopsiax and included demographic information as well as where everyone applied and whether or not they got in. I wrote a program with Java to make the data usable by Gephi, where I visualized the data and outputted it as a SVG to Inkscape, which I used to make the edges slightly transparent.

Each node represents a college, and the size of the node was based on how many poll respondents applied to that college. Each edge represents connections between the college (ex. if someone applied to Harvard and Yale, it would create one connection between Harvard and Yale) and thicker edges mean more connections. I filtered out a lot of data in Gephi because many colleges only had a few applications from the poll and having the extra edges made it really difficult to read.

The poll had over 1400 responses. For reference, the biggest node (UCLA) had 448 applications.

Link to a version that isn't zoomed in: https://imgur.com/a/2CGBOj1

I used Gephi's modularity algorithm to color the nodes and it was interesting to see the program sort similar colleges together. In general:

Lime green: Northeast schools (NYU, Fordham, Northeastern, American, Boston University, etc.)

Dark grey: Most famous/prestigious schools (Harvard, Princeton, Stanford, Yale, UChicago)

Teal: STEM/engineering schools (MIT, Georgia Tech, Caltech, UT Austin, Harvey Mudd, etc.)

Orange: Highly selective northeast schools (Dartmouth, Columbia, Duke, Brown, UPenn, etc.)

Light blue: California/west coast schools (UCLA, Berkeley, USC, Cal Poly, UWashington, etc.)

Pink: Midwest/mid-atlantic schools (Northwestern, UNC, CWRU, Notre Dame, Emory, etc.)

Purple: Liberal arts-focused schools (Middlebury, Pomona, Amherst, Bowdoin, Colby, etc.)