Personally Relevant Content  Based On Social Connections
Team <ul><li>M. Deniz OKTAR, BSc @ Koc University, Istanbul </li></ul><ul><li>Firat GELBAL, MSc @ TU/e, Eindhoven </li></u...
Problems <ul><li>No psychological or social aspect </li></ul><ul><li>Rapidly emerging online media content like news feeds...
Value Proposition <ul><li>Wisdom of the Crowd vs. Circle of Trust </li></ul><ul><li>Social added value </li></ul><ul><li>3...
+ + Individual Interests + + + + + + + + + + + + Politics Technology Music Sports Relevance =  α  ∙ Content +  β  ∙ CF +  ...
+ + + + + + + + + Network Interests + + + + + + + Relevance =  α  ∙ Content  +  β  ∙ CF +  θ   ∙  Social Relevance =  α  ∙...
+ + + + + + + Circle of Trust Interests + + + + + + + + Relevance =  α  ∙ Content +  β  ∙ CF  +  θ   ∙  Social Relevance =...
+ + + + + + + + Interests’ Reconfiguration + + + + Relevance =  α  ∙ Content +  β  ∙ CF +  θ   ∙  Social
+ + + Interests’ Reconfiguration + + + + Sports Proximity + + + + +
+ + Interests’ Reconfiguration + + + + Politics Proximity + + + + + +
Smarter Social Ads <ul><ul><li>Social Advertising:  </li></ul></ul><ul><ul><li>“ If your friends have it, then you will  h...
Thanks <ul><li>Focus on developing the recommendation system. </li></ul><ul><li>Add value to your social network. </li></u...
Questions? <ul><li>New User/Critical Mass P oblem </li></ul><ul><li>Social Capital </li></ul><ul><li>Importance of Trust <...
Critical Mass Problem BACK Solution:  Hybrid Engine
Trust is Value BACK
Social Capital BACK
Why Different <ul><li>Social Added Value </li></ul><ul><li>Live Social Graphs </li></ul>BACK vs live updates on social gra...
Chinese Song Problem BACK Time Songs of American User Relevance Songs of Chinese User Radiohead – Paranoid Android +++ Col...
Social Noise <ul><li>Iletken uses Social Noise instead of Random </li></ul>BACK Noise = Random(t); vs Noise = Social Capital
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Personally Relevant Content Based On Social Connections

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Personally Relevant Content Based On Social Connections

  1. 1. Personally Relevant Content Based On Social Connections
  2. 2. Team <ul><li>M. Deniz OKTAR, BSc @ Koc University, Istanbul </li></ul><ul><li>Firat GELBAL, MSc @ TU/e, Eindhoven </li></ul><ul><li>Baris Can DAYLIK, BSc @ Koc University, Istanbul </li></ul><ul><li>Selcuk ATLI, MSc @ RPI, New York </li></ul><ul><li>Board of Advisors: </li></ul><ul><li>Prof . James Hendler, Professor in Computer Science @ RPI, TWC </li></ul><ul><li>Dr. Tarcan Kumkale, Assist. Prof. in Psychology @ Koc </li></ul><ul><li>Dr. Oznur Ozkasap, Assist . Prof . in Computer Science @ Koc </li></ul>
  3. 3. Problems <ul><li>No psychological or social aspect </li></ul><ul><li>Rapidly emerging online media content like news feeds need special engine </li></ul><ul><li>Computation time </li></ul><ul><li>New user issue </li></ul><ul><li>Critical mass problem </li></ul><ul><li>Overspecialization </li></ul><ul><li>Explicit feedback </li></ul>
  4. 4. Value Proposition <ul><li>Wisdom of the Crowd vs. Circle of Trust </li></ul><ul><li>Social added value </li></ul><ul><li>3-layered Hybrid Engine </li></ul><ul><li>Weighted social proximity graphs </li></ul><ul><li>Multiple social graphs for different interests </li></ul><ul><li>Implicit/explicit feedback </li></ul>vs 14 C It rains heavily in Eindhoven. Firat says: It rains heavily in Eindhoven.
  5. 5. + + Individual Interests + + + + + + + + + + + + Politics Technology Music Sports Relevance = α ∙ Content + β ∙ CF + θ ∙ Social Relevance = α ∙ Content + β ∙ CF + θ ∙ Social
  6. 6. + + + + + + + + + Network Interests + + + + + + + Relevance = α ∙ Content + β ∙ CF + θ ∙ Social Relevance = α ∙ Content + β ∙ CF + θ ∙ Social
  7. 7. + + + + + + + Circle of Trust Interests + + + + + + + + Relevance = α ∙ Content + β ∙ CF + θ ∙ Social Relevance = α ∙ Content + β ∙ CF + θ ∙ Social
  8. 8. + + + + + + + + Interests’ Reconfiguration + + + + Relevance = α ∙ Content + β ∙ CF + θ ∙ Social
  9. 9. + + + Interests’ Reconfiguration + + + + Sports Proximity + + + + +
  10. 10. + + Interests’ Reconfiguration + + + + Politics Proximity + + + + + +
  11. 11. Smarter Social Ads <ul><ul><li>Social Advertising: </li></ul></ul><ul><ul><li>“ If your friends have it, then you will have it ” </li></ul></ul><ul><ul><li>People are influenced by their friends </li></ul></ul><ul><ul><li>iletken captures people that most influence their friends </li></ul></ul><ul><ul><li>Opinion leaders are easy to find </li></ul></ul>
  12. 12. Thanks <ul><li>Focus on developing the recommendation system. </li></ul><ul><li>Add value to your social network. </li></ul><ul><li>For more information: www.iletken-project.com </li></ul>
  13. 13. Questions? <ul><li>New User/Critical Mass P oblem </li></ul><ul><li>Social Capital </li></ul><ul><li>Importance of Trust </li></ul><ul><li>Why Different </li></ul><ul><li>Chinese Song Problem </li></ul><ul><li>Social Noise </li></ul><ul><li>Thanks </li></ul>
  14. 14. Critical Mass Problem BACK Solution: Hybrid Engine
  15. 15. Trust is Value BACK
  16. 16. Social Capital BACK
  17. 17. Why Different <ul><li>Social Added Value </li></ul><ul><li>Live Social Graphs </li></ul>BACK vs live updates on social graphs 14 C It rains heavily in Eindhoven. Firat says: It rains heavily in Eindhoven.
  18. 18. Chinese Song Problem BACK Time Songs of American User Relevance Songs of Chinese User Radiohead – Paranoid Android +++ Coldplay – X&Y Oasis – Wonderwall ++ Blur – Coffee and TV Greenday – Good Riddance +++ Foo Fighters – Big Me ... ... Franz Ferdiand – Take me Out
  19. 19. Social Noise <ul><li>Iletken uses Social Noise instead of Random </li></ul>BACK Noise = Random(t); vs Noise = Social Capital

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