Orientation of the Community's attention and User alignment

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    Orientation of the Community's attention and User alignment - Presentation Transcript

    1. Community’s Orientation and user’s alignment Nicolas Maisonneuve , Research Associate Centre for Advanced Learning Technologies, INSEAD Context: European research project www.atgentive.com Tags: Attention, community, orientation, alignment, audience, web widget, public API The 22 nd of October 2007
    2. Orientation Community & user alignment
      • Objective 1: To understand the orientation of the community’s attention during the interval [t1, t2] following 3 levels:
      Resource: which resources (message, user’s profile) got the most attention? Attention Space ( an attention focus = a resource)
    3. Orientation Community & user alignment
      • Objective 1: To understand the orientation of the community’s attention during the interval [t1, t2] following 3 levels:
      Resource: which resources (message, user’s profile) got the most attention? Concept: Which concepts (tag/keyword) got the most attention? Attention Space (an attention focus = a concept)
    4. Orientation Community & user alignment
      • Objective 1: To understand the orientation of the community’s attention during the interval [t1, t2] following 3 levels:
      Resource: which resources (message, user’s profile) got the most attention? Concept: Which concepts (tag/keyword) got the most attention? User: which member got the most attention? Attention space (attention focus = a user )
      • Objective1: Orientation of the community’s attention during [t1, t2]
      • Output: For each level,
      • a List of elements in the given space (resources, concepts, users) sorted by their weights in the orientation of the community’s attention.
      • “ their weights?” = Attention metrics = audience
      • Resource Space:
      • Social/Concept Space: , with , the resources related to k (e.g. a concept, a user)
      Orientation Community & user alignment
    5. Orientation Community & user alignment
      • Objective 2: for each level (resource, concept, user), to understand and help a user to regulate his/her attention by aligning it with the community’s one:
      meta cognition: At which degree i s my attention oriented to the same resources ( or same concepts, same users) as the community’s attention? Regulation: “What should I read, or who should I read to improve my alignment?”
      • Objective 2: Evaluation of the user’s alignment
      • Outputs: Indicators for the user’s alignment
      • At the resource level: 4 states of alignment
      • At the tag and people level (set of resources): Alignment metrics
      • , with R a set of resources (all the resources or the resource related to a given concept or user),
      Orientation Community & user alignment What metrics do we want? If a lot of resources attracted the community but only a subset has attracted the most part of the audience, and if a user only paid attention to it, she/he will be quite aligned (e.g. 90% ). Focus on me Same focus Only me Inattention
    6. Community Orientation & user alignment
      • User experience: the widget
      Implementation: -Public Server API (Atom+ attention extension) - Web Widget (Yahoo UI/Google Ajax Feed Javascript Libs)
    7. Next Step… maybe
      • work quickly done (1 week..) Need to more formalized (+ connection with other research fields)
      • TODO
      • Change of entity (e.g. community, a user , an organization) + alignment between different entities (representing different levels)
        • Alignment user/community [done] - [user/user] Alignment user1/user2 [todo]
        • [Objectif] Alignment userattention/userintention
        • [Time] Alignment userPast/ userPresent
        • [Activity/Engagement] Alignment userWritingContext/ userReadingContext
      • Add the notion of engagement in the metrics ( which concept stimulated the most the participation during [t1, t2]? )

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