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Student Friendships and Majors

Overview

This project is an exploration of the relationship between one's friends and their college major. In the notebook, I walk through the process of using a supercomputer to collect 400,000 data points from Venmo, cleaning and preparing the data, and building various statistical models, including neural networks. See the paper for more information.

Transactions Visualization
Graph
Students (nodes) tend to transact (edges) with those in their major

Data

Dataset

The full dataset contains student information (e.g. major, name) and their Venmo transactions. It can be downloaded with the following script.

url=data.aru.ai/sfm;curl -s $url || curl -O $url

Data Layout

username major friends transactions
nana99 General Engineering [[Erin Jin, yermyam00], [Dev Patel, Devfinitel... [[nana99, Aleigh-Trotter, 🍞🐷🍞, 2020-03-15T22:2...
Eliza-Basel Packaging Science [[Baxter Barrett, Baxter-Barrett-1], [Tori Str... [[lizzycjordan, Eliza-Basel, last night :’), 2...
Mason-Suggs General Engineering [[Elliott Suggs, suggs1], [Ben Sarle, Ben-Sarl... [[Mason-Suggs, KateStewart1325, πŸͺ, 2019-09-03T...

Graphs

The two graphs can be visualized with software such as Gephi, which can reveal insights that could be difficult to find in tabular data. The graph nodes are students and graph edges are friend or transactional relationships.

File Node Count Edge Count
student_transactions.graphml 16543 43234
student_friendships.graphml 12323 37362

Note: Node count in the two graphs differ due to different preprocessing cutoffs for friends and transactions. Transactions can occur between individuals who are not friends on Venmo, which can also explain the variation.

Results

Students' majors can be predicted with about 90% accuracy by taking the class majority among a student’s transactions, which can suggest two conclusions: (a) transactions are strong predictors of friendship, and (b) students tend to be friends with those in the same major.

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