A Testbed for Evaluating and Visualizing Facebook Friend-list Recommendations Public Deposited

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Last Modified
  • February 26, 2019
Creator
  • Wu, Ziyou
    • Affiliation: College of Arts and Sciences, Department of Computer Science
Abstract
  • This project focuses on evaluating named group recommendation algorithms and analyzing the recommendation output. Our approach is developing a Facebook-based testbed for evaluating how the recommendation can reduce user’s effort to create friend-lists and visually validating the recommendation results. The testbed has three components: a recommendation engine, a friend-list editor, and a tool for visualizing recommendations. The recommendation engine implemented in Facebook mines social graphs to make predictions on friend-lists. The Friend-list Editor allows editing recommendations and measures the efforts a user takes to create friend-lists with and without recommendations. The visualization tool provides a set of visualization methods of social graphs and friend-lists.
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Rights statement
  • In Copyright
Note
  • Funding: None
Advisor
  • Dewan, Prasun
Degree
  • Bachelor of Science
Honors level
  • Honors
Degree granting institution
  • University of North Carolina at Chapel Hill
Extent
  • 35 p.
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