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Flickr Slow Social Network Intelligence Systems

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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 - PowerPoint PPT Presentation

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Page 1: Flickr

FlickrSlow Social Network Intelligence Systems

Page 2: Flickr

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

Page 3: Flickr

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

Page 4: Flickr

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”

Page 5: Flickr

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

Page 6: Flickr

Upload anywhere Upload from:

Browser Desktop App Mobile Device Third Party Apps

Page 7: Flickr

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

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Beginning of Social Network

Page 9: Flickr

Enumeration Rapid growth Countless users in the beginning (Early

Adopters) Low network connectedness New members join more quickly than

friendships can be established

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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

Page 11: Flickr

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

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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

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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

Page 14: Flickr

Petri Net

Page 15: Flickr

Everyday Use of Established Social Network

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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

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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

Page 18: Flickr

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

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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

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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

Page 21: Flickr

Petri Net

Page 22: Flickr

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, Masoud Valafar, Reza Rejaie, Walter Willinger

Typical Examples of Slow Intelligence Systems, Yingze Wang