This project focuses on the type of personal traits that can be inferred about an individual based on his/her location data. Factors affecting inference accuracy include the length of time over which data is collected from participants and the frequency of location points recorded over the collection period. To gather data, I will develop a mobile app which participants will allow to sample their location at random points throughout the day and ask the users to give some context about the points collected. Other participants will then be asked to infer general information about those individuals using some of their location data. This project’ s results have major implications in user privacy, especially on social media, and they may make users and corporations more aware of potential risks.

I have enjoyed working on different UROPs in the past, and I am excited to spend more time researching through SuperUROP. User privacy is a new field for me and has a big impact today, so I look forward to using my experience in user interface design and data analysis to explore this topic. Through SuperUROP, I would like to learn more about communicating research results rather than just producing them in a lab.