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Flickr

Flickr. Slow Social Network Intelligence Systems. Share your photos. Watch the world. Yahoo service Upload pictures/albums Make friends and share images Edit pictures Over 4 billion photos. Photo sharing. Choose who can comment on your photos Add notes to your photos

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Flickr

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  1. Flickr Slow Social Network Intelligence Systems

  2. Share your photos.Watch the world. • Yahoo service • Upload pictures/albums • Make friends and share images • Edit pictures • Over 4 billion photos

  3. Photo sharing • Choose who can comment on your photos • Add notes to your photos • Favorite yours and others photos • Tag people in your photos • Categorize your photos

  4. Friending • Search people by name or email • Import contacts from Yahoo! Mail, Gmail, or Hotmail • Invite friends by email • Categorize friends as “family” or “friend” • Share photos with non-users through a “Guest Pass”

  5. Uber Social • Connect your Flickr account to: • Facebook • Twitter • Blogging tools • Yahoo! Updates • Add Flickr “Badge” to your website • Embed a slideshow on your website

  6. Upload anywhere • Upload from: • Browser • Desktop App • Mobile Device • Third Party Apps

  7. Photo Grouping • Add location/tags • Geotag vacation photos • Add to previous collections or create new ones • Public collections like NASA Goddard Space Flight Center, White House photostream, Library of Congress, Smithsonian, US National Archives

  8. Beginning of Social Network

  9. Enumeration • Rapid growth • Countless users in the beginning (Early Adopters) • Low network connectedness • New members join more quickly than friendships can be established

  10. Propagation • Period of ongoing growth in which both membership and linkage increases • Early adopters form links between themselves and other users • Users share multitudes of photos

  11. Adaptation • New users start out as power users • Settle into their user class • Singletons • Middle region • Giant component • Stay at this level for the rest of their membership

  12. Elimination • Singletons contribute little to the social network • Their photos are only viewed by them • Lack of contribution or all out abandonment of the social network • Can be considered to no longer be a part of the social network • Giant component and Middle region become the driving force of the social network

  13. Concentration • Views, comments, faves, tags • Top contributors • Members of the Giant component • Showcase the best the social network has to offer • All the photos that users decide to share with the world

  14. Petri Net

  15. Everyday Use of Established Social Network

  16. Enumeration • Users have established profiles and set of friendships • Prepare photos for addition to social network • Create photo albums to store their newly uploaded photos • Possibly geotagged and/or commented

  17. Propagation • Sharing of photos/albums to friends in network • Makes links between users and friends stronger • May make albums public and share with entire network • Adds content to network

  18. Adaptation • Change in users and photos transparency • Public vs. Private • Making photos public adds more value to the network as a whole • Making photos private (only visible by friends) limits the exposure along the network • Personal preference

  19. Elimination • Photos that are not viewed or shared • Have no bearing on the network itself • Contribute very little to the overall user’s experience • These photos will be lost among the more popular albums

  20. Concentration • Similar to previous model concentration • Focus is more on photos and network content • Network becomes concentrated on popular photos/albums • Popularity determined by comments/faves/views

  21. Petri Net

  22. References • Social Network Analysis: An Approach and Technique for the Study of Information Exchange, Caroline Haythornthwaite • Structure and Evolution of Online Social Networks, Ravi Kumar, Jasmine Novak, Andrew Tomkins • Beyond Friendship Graphs: A Study of User Interactions in Flickr, MasoudValafar, Reza Rejaie, Walter Willinger • Typical Examples of Slow Intelligence Systems, Yingze Wang

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