Collective stream and metadata june 2010 by PeopleBrowsr
 

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PeopleBrowsr presents Collective Stream & Metadata June 2010 ...

PeopleBrowsr presents Collective Stream & Metadata June 2010

The Collective Stream and Meta Data Cloud is profoundly changing the way we write code, analyze events.
Vast dynamic data stores power collective consciousness

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Collective stream and metadata june 2010 by PeopleBrowsr Presentation Transcript

  • 1. The Collective Stream and the Metadata Cloud A June 2010 Review Jodee Rich CEO PeopleBrowsr
  • 2. HUMAN SOCIALISATION Swinging through the trees..
  • 3. HUMAN SOCIALISATION Emerging from the jungle with Language The Collective Stream and Metadata – June 2010
  • 4. HUMAN SOCIALISATION Thousands of years later we wrote it down
  • 5. HUMAN SOCIALISATION PCs, the internet, cell phones have come together to enable a vast distributed network of human intelligence
  • 6. HUMAN SOCIALISATION A Persistent Stream of Consciousness..
  • 7. HUMAN SOCIALISATION Established Infrastructure, the Stream and the Meta Cloud
  • 8. HUMAN SOCIALISATION Persistent Open Meta Framework displaces established Infrastructure
  • 9. HUMAN SOCIALISATION Government Intervention
  • 10. HUMAN SOCIALISATION Collective Consciousness and Industry Disruption – May 2010 Stream Dries up…
  • 11. HUMAN SOCIALISATION Or WE adapt..
  • 12. 1 YEAR OF TWITTER TRAFFIC: View chart and stats on analytic.ly Now at 50 Million Tweets/day
  • 13. BRAND METADATA - 1 MILLION BRAND MENTIONS PER DAY
  • 14. 2010 OPENNESS Little Twitter is dragging the others out of the cave and into the open Openness and Diversity is fundamental to a Meta Data System
  • 15. OPENNESS Because it is open, the Twitter Stream will become the core transport layer for rich MetaData and Cross Network Links
  • 16. Social Meta Data Examples Links Sentiment Hashtags Likes ReTweets Influence. Eg Klout Extended Profile Brand Pics Lists Personas. Eg Tlists Connections Relatedness Cross Media Rels
  • 17. CASE STUDIES IN MAY 2010 ABC Hotlist Sony Pictures Comcast Entertainment Airline Sentiment eBay Toyota Recall Super Bowl Ads UK Elections Music Influencers in New York
  • 18. ABC TWEETERS HOTLIST Merge Corporate Exec profile metadata
  • 19. Goal: Evaluate impact of Traditional Media on the Social Media sphere Build engaged audience Solution: 180 day Historical Analysis of Posts overlay on TV Ad spend metadata and other channels Performance and Results Identified type of ads that produce the best audience response 50% fluctuation on engagement based on time of message release
  • 20. Industry : Media Entertainment Goals: Promote a Network TV Premiere Create online Buzz during the Event Performance and Results N umber 1 Twitter Trending Topic during Premiere Over 17,000 mentions of the #Hashtag during the week of the Premiere
  • 21. Airline Sentiment Metadata merging Mechanical Turk with the Twitter Stream. 95% accuracy Vs 70-80% automation alone US AIRLINE INDUSTRY STUDY JUNE 2009
  • 22. Seek an effective way to measure brand sentiment accurately. The goal is to find a list of influencers speaking in both positive and negative terms and engage. Call center to respond to negative sentiment metadata everyday Velocity 10,000 Mentions/day filtered to 180 Meaningful comments
  • 23.
    • Analytics:
      • Overlayed Sentiment , Brand and Ad Metadata
      • Effect of Traditional Media on Social Media
      • Mechanical Turk to measure accurate Sentiment
      • Metrics to measure Success:
        • Total Mentions
        • Positive Mentions
    By Volume Mullen and Radian6 SUPER BOWL Collective Consciousness and Industry Disruption – May 2010
  • 24. SUPER BOWL
    • Results:
      • 103,158 Total Mentions
      • Sampled 1000 Tweets from Every Brand and used Mechanical Turk Human Sentiment to analyze
      • Polarized:
        • 50% Positive
        • 28% Negative
        • 18% Neutral
    Collective Consciousness and Industry Disruption – May 2010
  • 25. SUPER BOWL Collective Consciousness and Industry Disruption – May 2010
  • 26. SUPER BOWL Correlation of Tweets and Ads
  • 27. UK ELECTION DASHBOARD
  • 28.
    • Top Bands:
    • Mgmt
    • Vampire Weekend
    • Passion Pit
    • Anamanaguchi
    • Animal Collective
    • The Strokes
    • Researched 900 bands in NY Extracted mentions of each in the last 6 months Selected most mentioned
    NEW YORK MUSIC INDUSTRY
    • Top Music Influencers:
    • @Jimmyfallon
    • @Nytimes
    • @TheOnion
    • @johnlegend
    • @maddow
    • @InStyle Influencers – extracted biggest music labels/accounts followers + everyone in NY on Twitter directory + NY users under music/venues Twitter lists
    Persona Metadata
  • 29. SMS is the benchmark Twitter, Facebook and the other networks are still small, 150 Million posts/day combined SMS is over 7 Billion/day SCALE..ITS EARLY DAYS
  • 30. Mentions, RTs, … Comments, Sharing,… Profiles, Comments, … Status Updates, Comments, … Pictures, Comments, … Connections, Comments Blogs Mentions, … Fan Pages SMS CROSS PLATFORM INTEGRATION
  • 31. THE NEXT TWO YEARS The Conversation Stream becomes the Conversation Cloud A real time historical record Meta Data Hyperlinks become People Hyperlinks
  • 32. THE NEXT TWO YEARS The Conversation Cloud becomes the Rich Meta Data Cloud Social Meta Data Cloud will become the core backbone for people data
  • 33. EXPERIMENTAL APPS What can we build? T2 Contextual Search and Post Artificial Intelligence - AI Cloud powered Q and A
  • 34. EXPERIMENTAL APPS AI What can we build? In the past the quest for AI has been driven by machine learning projects. They have been Training and CPU intensive
  • 35. EXPERIMENTAL APPS AI What can we build? Artificial Intelligence AI is now Build a database of Questions and Answers from the Twitterverse Crowdsource Questions without Answers – Crowdflower Devote CPU cycles to contextual analysis and NLP Artificial Intelligence AI was about machine learning or CPU cycles For the first time we have a vast open database of Questions and Answers Lets turn the problem upside down..
  • 36. EXPERIMENTAL APPS T2 What can we build? T2 Contextual Search and Post Inline Content T2 HyperLocal Linked to other netwoks
  • 37. EXPERIMENTAL APPS T2
  • 38. EXPERIMENTAL APPS T2
  • 39. VAST DYNAMIC DATA STORES POWER COLLECTIVE CONSCIOUSNESS
  • 40. REFERENCES This Deck http://bit.ly/ www.Analytic.ly Socialnomics09 PeopleBrowsr Super Bowl Study PeopleBrowsr Top 20 Brands Study http://www.s lides hare.net/peoplebrowsr/the-twitter-metadata-revolution-and-collective-consciousness http://www.nytimes.com/external/readwriteweb/2010/05/17/17readwriteweb-twitter-forefather-leaves-aims-to-disrupt-b-89770.html http://blogs.hbr.org/research/2010/05/why-gallup-when-you-can-tweet.html http://www.briansolis.com/2010/05/report-top-20-brands-on-twitter-april-2010/