Morgan A. Madeira
Anupam Joshi, Professor, Department of Computer Science and Electrical Engineering
UC Ballroom | 10:00-12:30 PM
Social media has increasingly become an outlet for expression for a large part of our society. Literature suggests that analyzing data from these sites can lead to improvements in areas such as health-care and search-ad targeting. Users of these sites often associate with many other users described as “friends,” even if they do not have a strong connection, or what would be described as friendship in daily life. It is valuable to determine the strength of relationships between users and to identify communities within social networks. These communities represent people with similar characteristics, which are used by applications to solve many real-world problems. For instance, it is useful to identify groups that listen to the same type of music, are similarly affected by a natural disaster, or share health risks for a particular disease. We have created a system to collect and analyze the data about user characteristics, while being respectful of privacy concerns. The system is composed of a front end Facebook application and a back end machine-learning based tool. The front end component gathers data about a user and their friends. The back end uses the collected data and machine-learning techniques to determine relationships between users.
This work was funded through an Undergraduate Research Award from the UMBC Office of Undergraduate Education.
