With a Little Help from My Friends: Personalization via Friendsourcing

1. With a Little Help from My Friends:Personalization via Friendsourcing Michael Bernstein mitcsail mit human-computer interaction

2. Information Overload New York Times Facebook Twitter Engadget Slashdot Ffffound! xkcd PostSecret Cake Wrecks Camels and Chocolate Stereogum Television without Pity Fat Cyclist Lifehacker Cute Overload Gawker Confessions of a Pioneer Woman Digg Reddit

3. Information Overload Number of Posts 0 Relevance to You An Open Letter to Lance Armstrong(UPDATED x 3) Fat Cyclist It Was All Gravy Until Meningitis Came Into Play Camels and Chocolate Exhibit Transforms Your Spreadsheet into an Interactive Web Page Lifehacker Humanities Ph.D.s Are Anticipating Hard Times New York Times

4. Social Filtering E-mail Social Networks To: Michael Bernstein <msbernst@mit.edu> From: Rob Miller rcm@mit.edu Interesting article about a designer who jumped ship from Google to Twitter because he felt shackled by all the A-B testing. http://www.nytimes.com/2009/05/10/business/10ping.html

5. Your friends, family and colleagues know your interests, activities, and personality.

6. Friendsourcing:Your friends, family and colleagues know your interests, activities, and personality – and use it to help you.

7. Active Information Seekers

8. Survey Investigation N = 100 • Are the people who spend time seeking web content also sharing it? “I rely on tools that aggregate popular web content from many sources: for example, Google News, Google Reader or Digg.” “I often seek out entertaining posts, jokes, comics and videos using the internet.” “I spend a large amount of free time viewing web content.” “I often tell people I know about my favorite web sites to follow.” “When I see something I like on the internet, my first thought is often, ‘Who else would enjoy seeing this?’” “I often post interesting web content to public places like my IM status, my Facebook profile, or Digg.”

9. Yes: Sharers are Seekers • Over 50% of anindividual’s interestin sharing wasexplained by theirinterest in seekingR2 = .53, p < .001 • Social capitalhas an almost negligible effectAdj. R2 = .55

10. FeedMe • Designed to facilitate and amplify the sharing process • Foregrounds sharing and suggests friends who might be interested in posts being read

11. FeedMe • Concern: it can be difficult to judge relevance, and it’s work to send an e-mail • FeedMe: Lowers the relevance and effort barriers • Concern: what if I spam my friends? • FeedMe: makes visible relevant information rcm@mit.edu Recommend to: msbernst@mit.edu Send 1 today 0 today rcm@mit.edu rcm@mit.edu 0 today 10 today

12. Vector Space Model Friend A: sports: 200 baseball: 150 sox: 132 lacrosse: 89 workout: 41muscle: 30hiking: 23vitamin: 22 New post: Friend B: design: 184 tweet: 170 web: 79 twitter: 48 social: 43friendfeed: 32blog: 25developer: 23

13. Ongoing work • Palo Alto Research CenterCan we help business and individuals create and manage huge amounts of friend feed information? x 100

14. To: Michael Bernstein <msbernst@mit.edu> From: Rob Miller <rcm@mit.edu>, David Karger <karger@mit.edu>,Adam Marcus <marcua@mit.edu> Cc: Naveen Sharma <naveen.sharma@xerox.com> Michael, you should probably check this out ...