Smx March 2010 Bing Realtime Social
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Smx March 2010 Bing Realtime Social

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Sean Suchter's presentation on Bing Realtime Search at SMX West 2010

Sean Suchter's presentation on Bing Realtime Search at SMX West 2010

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Transcript

  • 1. Bing Social Search
    Sean Suchter
    General Manager
    Search Technology Center Silicon Valley
  • 2. Why do search engines care?
    Users expect to know right now
    Did I just feel an earthquake?
    What’s going on with the Giants game?
    Is my cell network down?
    Challenges
    Keeping up with the speed
    Make sense of massive content
    Relevance is still expected
    2
  • 3. Twitter (+ social media) content
    Timely (but not always accurate!)
    Opinionated – feelings, reactions, impressions
    Brief
    Context is often essential to determine meaning
    Who said it, where, to whom
    References - @user, #hashtag, RT, favorites, follows
    Content creation follows attention
    Self-organized communities of attention
    If there’s no content, you can ask for some
    Observable propagation of information
  • 4. Use Case: Breaking Local News
    Power outage 8am on February 17, 2010 in Palo Alto
    Out for everyone or just me?
    No media or online news
    No web search results (B, G, Y)
    Fast awareness through local social network
    Useful public social search results in minutes
    Meta-Data
    Url referrals
    Retweet counts
    Primary data
    Images
    Tweet/Blog content
    Low Latency
    Within minutes
    Voice of the People
    Non-official content
  • 5. Publication Platforms
    Web
    Public
    Answers
    Twitter
    Facebook
    Access
    Community
    Email
    Private
    Public
    Community
    Private
    Publication
  • 6. To rise above the noise, there is more to do as search gets more social
    Plus…
    6
  • 7. Topic / sentiment range, volume, trend analysis
    What is the baseline rate of mentions / sentiment per unit time?
    Look for changes in attention flow around a subject, location, topic
    Watch for correlated signals from multiple sources
    Consider source relevance and authority as well
  • 8. Graph analysis for relevance and ranking
    Spam marketing campaign
    (teeth whitening)
    Naturally connected community (#smx)
    Real time relevance needs data mining to filter and rank based on history
    Spammy communities can be highly visible
    Social graph, topic/concept graph, and behavior/gesture graphs are all useful tools
  • 9. bing.com/twitter at a glance
    Top Tweets
    Top Shared Links
    Top Tweets/
    Sentiment per link
    Adult / Spam filter; Tweets/Links ranking & relevance
  • 10. Thank you