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

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

25. SUPER BOWL Collective Consciousness and Industry Disruption – May 2010

26. SUPER BOWL Correlation of Tweets and Ads

27. UK ELECTION DASHBOARD

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/