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Tagging from personal to social

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This is for a keynote I gave at WWW 06 in Edinburgh

This is for a keynote I gave at WWW 06 in Edinburgh

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    • 1. Tagging – From Personal to Social: Some Observations & Design Principles Rashmi Sinha Uzanto
    • 2. Structure of Talk
      • My Perspective
      • Tagging on a Personal Level
        • Compared to categorization
      • Social Systems formed by Tagging
      • Tagging & Wisdom of Crowds
      • Some weaknesses
      • 9 Design Principles
    • 3. Cognition in the wild
      • Cognitive Anthropology: Understanding culture by understanding cognition
      • Two main methods
        • Pile Sorting
        • Freelisting
    • 4. Free-listing
      • Goals
        • Explore boundaries & scope of domain
        • Capture cultural consensus
        • Gain familiarity with user vocabulary
      • Strengths
        • Simplicity
        • Flexibility
          • Conducted as part of interview, or as written exercise
        • “ Name all the x's you know.”
    • 5. Digital Categorization Multiple concepts activated Choose ONE of the activated concepts. Categorize it! Object worth remembering (article, image…) Analysis-Paralysis!
      • Analysis Paralysis
      • Balancing your scheme
      • Over time – category boundaries change, labels obsolete
    • 6.
      • Cannot place in more than one place
      • Disappears from view
      • Mistakes are costly
    • 7. Tagging is simpler Multiple concepts are activated Tag it! Note all concepts Object worth remembering (article, image…)
      • Goal is to categorize
      • Maps to cognitive process
      • Reduced load
      • Fun, Self-feedback, social feedback
      • Less balancing of scheme
    • 8. Tagging still leads to anxiety
      • Differs from person to person
        • And by domain
      • Solution not simpler input process (though that could help)
        • Confidence in finding
    • 9. Some hypothesis
      • Tagging takes lesser time than categorizing
        • Users generate tags/categorize for new emails / bookmarks
        • Measure : Time to categorize compared to time for 1 OR 2 OR 3 tags
      • Categories are more memorable than a tag
        • Give users 30 secs. per item to generate tag OR categorize
        • Measure : Recall of tag / category after a week
      • Comparing different types of tags
        • Personal tags are more memorable than Semantic ones
          • Measure : Tag recall after a week
        • Semantic tags are generated first
          • Measure : Order of Semantic and Personal tag generation
    • 10. Hypothesis (cont)
      • Hierarchy & non-exclusivity
        • Compare time taken
        • Recall
        • Difficulty
      (D) Categorization (C) Flat Categorization Exclusive (B) Hierarchical Tagging (A) Tagging Non-Exclusive Hierarchical Flat
    • 11. The Personal to the Social
    • 12. Browsing alone
    • 13. Along together
      • Alone together (Ducheneaut et al. CHI 2006)
        • Passive presence of others
        • Playing for the audience but not necessarily interacting
      • Social facilitation (Zajonc, 1960)
        • Improvement in performance in presence of others
        • Presence does not need to be active
        • Observed even in cockroaches!
    • 14. Tagging as second generation social network
      • Actually useful!
      • Lots of weak ties (Granovetter: The strength of weak ties )
        • Social networks emphasize strong ties (lists of contacts, friendship ratings)
      • Objects (tags) mediate social relationships
        • Objects are reasons people affiliate with each other
        • Provide context for relationship. Means for new relationships.
        • Theory: Object centered sociality (sociologist Karin Knorr Cetina)
      • Application: Interest based groups
        • Collaborative Tagging & Expertise in the Enterprise (John & Seligman)
        • Fringe Contacts: People Tagging for the Enterprise (Ferrell & Lau)
    • 15. Tagging and Wisdom of Crowds
      • Cognitive Diversity
      • Independence
      • Decentralization
      • Easy Aggregation
    • 16. 1. Cognitive Diversity
      • Need many perspectives for good answers
      • Groups become homogenous
        • Members bring less and less new information in
        • Varying levels of insight & knowledge provide good mix
          • Better than everyone having a lot of knowledge!
      • Diversity reduces groupthink
        • Groupthink works by shielding members from outside opinions
        • Rationalize away counterarguments
      • Diversity reduces conformity
        • Chance that you will change opinion to match group
    • 17. 2. Independence
      • Keeps people’s mistakes from getting correlated (uncorrelated mistakes averaged out)
      • Encourages people to bring in new viewpoints (diversity)
      • Concept of Social Proof
        • Milgram experiment
        • People assume that groups know what they are doing
        • Assuming crowd is wise, leads to herd like behavior
          • Can sometimes lead to good decisions
    • 18. 2. Independence (cont.)
      • Information Cascades
        • Sequence of uninformed choices, building upon each other
          • Example: Thai & Indian restaurant
          • Information is imperfect – sometimes incorrect, sometimes correct
          • Decisions made in sequence
            • Everyone relies on own information
            • And what everyone else is doing
            • Wrong information propagates down in a chain
        • Ideal when people make decision relying on private information
          • Compare Del.icio.us & digg
        • Information Cascades can be good
          • Example: Iowa farmers decision about hybrid corn
    • 19. Imitation & Suggestion
      • Intelligent & mindless imitation
        • Human beings are imitation machines
        • Imitation is a good thing
          • Bad when you don’t reply on private information
          • And don’t make independent judgment
            • Example: Japanese macaques learning to separate wheat from stones
        • Build some method to let people evaluate tag suggestions
      • Imitation & Suggestion in Tagging Systems
        • Lazy Sheep bookmarklet
        • Google Suggest approach
        • Towards the Semantic Web: Collaborative Tag Suggestions (Xu et al.)
        • Implicit Tagging using Donated Bookmarks (Markines, et al.)
    • 20. 3. Decentralization
      • Encourages independence
      • Takes advantage of tacit knowledge
        • People have specialized knowledge that might not be communicable to right person in centralized structure
        • Problems: Valuable information uncovered in one part of the system does not get communicated to another part
          • Need some type of loose coordination
      “ A crowd of decentralized people working to solve a problem on their own without any central effort to guide them, come up with better solutions, rather than a top-down driven solution.” Suroweicki
    • 21. 4. Easy Aggregation
      • A decentralized system can pick right solution
        • With easy way for information to be aggregated across system
      • Example: Francis Galton
        • A crowd of people made independent decisions
        • He added the votes
    • 22. Some Weaknesses of tag-based Social Systems
    • 23. 1. Tag Specificity, Expertise & Perspective
      • Shirky example: Dewey Decimals categorization of world religions
      • What about Flickr?
        • Hinduism: 6512 photos
        • Christianity: 5207 photos
    • 24. Tagging systems are better, but…
      • Tagging systems represent people who participate in them
        • Their viewpoints & perspective
      • Types of biases
        • In-groups might use more specific tags than Out-groups
        • Experts might use more specific tags than novices
    • 25. 2. No easy way to show minority viewpoint
      • Consensus viewpoint bubbles up
        • How to give alternative viewpoints a voice?
      • Example: Catholic Church recognizes Devil’s advocate
    • 26. 3. Why Amazon tags did not work
      • No clear articulation of benefits
      • Mixed with other, more common participation methods
      • Busy interface
      • No organic growth (seeding with select few)
    • 27.
      • Too many options?
    • 28. 4. Adoption by Average User
      • Tag navigation does not suit user task?
      • Users do not understand its for navigation?
    • 29. Design Principles for Tagging Systems
    • 30. #1: Make System Personally Useful
      • For end-user system should have strong personal use
        • Memorable Personal Snippets (e.g., Del.icio.us & Flickr)
        • Self-expression (e.g., Newsvine)
        • My expertise or interests (RawSugar)
      • Don’t count on altruism
        • System should thrive on people’s selfishness
        • Incent the behavior you want
      • Clearly communicate benefits to users
        • Create a positive reinforcement cycle
    • 31. del.icio.us Useful before Saving First Link
    • 32. #2:Identify Symbiotic Relationship Between Personal & Social
      • Individual participation in system should naturally aggregate into social stream
        • What personal snippets do people like to share?
        • Personal snippets > Social stream
          • Example
            • Pictures > Organized by Events
            • Music > Organized by Playlists
    • 33. #3: Make Porous Boundary Between Public & Private
      • Earlier systems
        • Personal (Personal Desktop Software, e.g., Picasa, EndNote)
        • OR Social websites (Shutterfly)
      • Rethink public & private
        • People will share for the right returns
        • Set defaults to public, allow easy change to private
          • Provide clear benefit of sharing
      • Give user control
          • Over individual pieces & sets
          • Delete items from history
          • Reset /remove profile
      Privacy settings on Flickr
    • 34. #4: Provide Outlet for Self-expression
      • Creative self-expression
        • Artistic expression (Flickr, YouTube)
        • Humor (YouTube)
      • Individual piece should be small
        • Can create sets & lists
        • Do Mashups
        • Simple, guessable URLs for everything
      • Leave room for games & social play
        • Appreciation
        • Stalking (some!)
        • Gossip
      Writers on Newsvine
    • 35. #4a. Allow for Different Types of Participation
      • Social sites don’t require 100% active participation
        • Implicit creation (creating by consuming)
        • Remixing—adding value to others’ content
      Source: Bradley Horowitz’s weblog, Elatable, Feb. 17, 2006, “Creators, Synthesizers, and Consumers”
    • 36. #4b. How to Encourage Participation
      • Insights from Social Psychology research
        • Highlight unique contribution
        • Allow for smaller local groups
        • Highlight benefit to self from participation
        • Highlight benefit to group
      Source: Using social psychology to motivate contributions to online communities, Ling et al. 2005
    • 37. #5. Provide Scent of Others in the System
      • What paths are well worn, what are not
      • User profiles / photos
      • Real-time updating
        • Feels like a conversation
        • sense that others are out there
      What people are digging right now!
    • 38. #6. And yet, Moments of Independence
      • Choreography: when alone, when part of group
      • Prevent mobs, optimize “wisdom of crowds”
      • Don’t make it too easy to mimic others
        • Incentives for originality & uniqueness
    • 39. #7. Enable Serendipity
      • Don’t make navigation all about popularity
        • Access to some popular stuff (keep this fast moving)
      • Make the “long tail” accessible
        • Use popularity as a jump off point to other ways of exploring
      • Provide personalization
        • Recommendations using collaborative filtering
          • Similar tags, content, others
      • Ad-hoc groups?
    • 40. #8. Allow for alternative viewpoints & perspectives
      • Tags bias perspective in specific manner
        • People of a group know more
          • Likely to use more specific tags
          • Hence less exposure (no hierarchy)
        • Similar problem for experts
    • 41. #9. Keep input simple. Solve problems with good findability
      • Tagging shows success of simplicity
        • Don't’ increase cognitive cost of tagging
      • Tagging systems can support different types of findability
        • Some metaphors
    • 42. #9a. User Experience for Faceted Browse Interfaces
      • User is in control
      • Every movement (forward, making a turn) is a conscious choice
        • System should provide information at every step
      • If user makes mistakes, she can go back or start again
      Like driving a car…
    • 43. #9b. User Experience with Recommender Systems
      • User has less control over specifics of interaction
      • System does not provide information about specifics of action
      • More of a “black box” model (some input from user, output from systems)
      Like riding a roller coaster…
    • 44. User Experience with Browsing Tagging Systems
      • Pivot Browsing
        • Move at a slower pace
        • Get the lay of the land, directly experience surroundings
        • Change paths when you want
        • Choose paths based on what looks promising, how well worn, what signs say
      Like a hike in the woods
    • 45. You can do all three with tags
      • Faceted Systems from Tags
        • Inducing Ontology from Flickr, Schmitz
      • Collaborative Filtering from Tags
        • Automatic Tag Clustering, Begelman, Keller & Smajda
      • Pivot Browsing on Tagging Systems
        • Tag-Based Navigation for Peer-to-Peer Wikipedia, Fokker et al.
    • 46. Parting thoughts
      • Tagging is in the eyes of the tagger
        • Can implicit tagging be tagging?
      • Tagging by others is more useful than tagging by self
        • Is tagging about harnessing consensus or personal perspective?
      • Will Categorization will be back?
        • Better interface
        • Non-exclusive
    • 47.
      • Questions?
      • [email_address]
      • URLs
      • www.uzanto.com
      • www.rashmisinha.com
    • 48.
      • “In essence tag systems mirror the pagerank structure of Google's system, but make the internal structures browsable and viewable directly.”
        • Lee Iverson

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