Thesis advisor: Sergio Alvarez / The recent explosion of online social networking through sites like Twitter, MySpace, Facebook has millions of users spending hours a day sorting through information on their friends, coworkers and other contacts. These networks also house massive amounts of user activity information that is often used for advertising purposes but can be utilized for other activities as well. Facebook, now the most popular in terms of registered users, active users and page rank, has a sparse offering of built-in filtering and predictive tools such as ``suggesting a friend'' or the ``Top News'' feed filter. However these basic tools seem to underutilize the information that Facebook stores on all of its users. This paper explores how to better use available Facebook data to create more useful tools to assist users in sorting through their activities on Facebook. / Thesis (BS) — Boston College, 2010. / Submitted to: Boston College. College of Arts and Sciences. / Discipline: Computer Science Honors Program. / Discipline: College Honors Program. / Discipline: Computer Science.
| Identifer | oai:union.ndltd.org:BOSTON/oai:dlib.bc.edu:bc-ir_102184 |
| Date | January 2010 |
| Creators | Epstein, Greg |
| Publisher | Boston College |
| Source Sets | Boston College |
| Language | English |
| Detected Language | English |
| Type | Text, thesis |
| Format | electronic, application/pdf |
| Rights | Copyright is held by the author, with all rights reserved, unless otherwise noted. |
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