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CLIQUE FINDER

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  1. CLIQUE FINDER By Ryan Lange, Thomas Dvornik, Wesley Hamilton, and Bill Hess

  2. PROBLEM - • How do friends form groups based on their Facebook activity or information? • Cluster friends based on their profile information and the relationships they share with other users on your friends list • Form cliques or groups of people within your friend’s list that may not have been considered before.

  3. SOLUTION • Facebook API • Clustering • Distance Metric • Home town, religion, images, shared friends, etc. • Bottom-up vs Top-down • Hierarchical • Max flow • Testing • Fake dataset • Varying sizes

  4. DATA SET • Some Data Restrictions • Cannot contain functionality that requests or collects Facebook usernames or passwords from any user; • Cannot store data received by Facebook for more than 24 hours • Cannot modify, rent, lease, loan, sell, distribute, or redistribute data to another part • Collectable Data • User’s Personal Data - gender, age, networks, relationship status, hometown, religious, status feed, etc • User’s Visible Data - wall post, comments, messages, notes, pages, notifications, events, groups, links, streams, friends, pictures, videos, tags, etc • Friend’s personal and visible data • All pictures that the user is tagged in

  5. DATA ADDS UP FAST • Testing Set – • About 7000 pieces of personal data • 40000 wall post • 350 photos, about • 1600 tags • tons of other miscellaneous data; such as status, events, links, notes, etc. • Data set includes at least 10 heavy users - • 70000 pieces of personal data • 400000 wall post • 3500 photos • 16000 tags • and much more miscellaneous data..

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