The document discusses how social media analytics can provide insights into collective human behavior and conversations online. It describes how tools can analyze large amounts of public social media data at scale, identifying influential users, measuring brand sentiment, and gaining understanding of topics and trends. Examples are given of social media analytics being used for marketing campaigns and conference events to improve outcomes. The future potential of social analytics is discussed, such as building a "rich metadata cloud" to gain insights from people's online interactions and conversations.

1. Hyper Analytics and the Collective Stream of Consciousness Jodee Rich CEO @PeopleBrowsr @WingDude Joe Fernandez CEO @JoeFernandez @Klout

2. HUMAN SOCIALISATION Hyper Analytics for Social Media – October 2010 Swinging through the trees..

3. HUMAN SOCIALISATION Emerging from the jungle with Language Hyper Analytics for Social Media – October 2010

4. HUMAN SOCIALISATION Thousands of years later we wrote it down Hyper Analytics for Social Media – October 2010

5. HUMAN SOCIALISATION PCs, the internet, cell phones have come together to enable a vast distributed network of human intelligence Hyper Analytics for Social Media – October 2010

6. HUMAN SOCIALISATION A Persistent Stream of Consciousness.. Hyper Analytics for Social Media – October 2010

7. HUMAN SOCIALISATION Established Industry, the Stream and the Cloud Hyper Analytics for Social Media – October 2010

8. HUMAN SOCIALISATION Persistent Social Framework displaces Industry Hyper Analytics for Social Media – October 2010

9. YEARS TO REACH 50 MILLION SUBSCRIBERS Radio 38 Years TV 13 Years Facebook 100 Million in less than 9 months Source: Socialnomics09 Hyper Analytics for Social Media – October 2010

10. “ That’s what social networking is all about: worshipping at the Altar of Self.” nothing more than an exercise in unashamed public vanity for the Look at Me generation” Sandra Lee in The Sunday Telegraph - May 25, 2008 PERCEPTION TWO YEARS AGO… Hyper Analytics for Social Media – October 2010

11. 1 YEAR OF TWITTER TRAFFIC: View chart and stats on analytic.ly Now at 50 Million Tweets/day Hyper Analytics for Social Media – October 2010

12. STREAM SIZE 2010: IT IS DAVID AND GOLIATH Next to Facebook, the Twitter Stream is still small Hyper Analytics for Social Media – October 2010

13. 2010 OPENNESS Little Twitter is dragging the others out of the cave and into the open Hyper Analytics for Social Media – October 2010

14. OPENNESS Because it is open, the Twitter Stream will become the core transport layer for rich MetaData and Cross Network Links Hyper Analytics for Social Media – October 2010

15. Hyper Analytics for Social Media – October 2010 EVERY BROADCST MEDIUM IS MEASURED

16. http://www.flickr.com/photos/moriza/126238642/ Hyper Analytics for Social Media – October 2010 THE INDIVIDUAL IS NOW THE BROADCASTER

17. Need to understand the network value of each customer and their ability to impact your brand Hyper Analytics for Social Media – October 2010 NETWORK VALUE IS A COMPONENT OF LIFETIME VALUE

18. Hyper Analytics for Social Media – October 2010 SIMPLE COUNTING IS NOT THE FUTURE OF ANALYTICS

19. Hyper Analytics for Social Media – October 2010 ANALYTICS CAN BE USED FOR MORE THAN JUST GRAPHS

20. 1 MILLION BRAND MENTIONS PER DAY Hyper Analytics for Social Media – October 2010

21. CASE STUDIES IN 2010 BlogWorld 2009 Starbucks eBay Toyota Recall Super Bowl Ads Hyper Analytics for Social Media – October 2010

24. Performance and Results 30% Percentage Increase in Relevant Followers 11,000 # of Mentions of the hashtag during the conference 39% # of Clicks Through CASE OVERVIEW: CONFERENCE 180,000 # of Tweets extracted for 360 days 171,423 Additional Followers reached by ReTweets 962 # of Users who ReTweeted the Message Hyper Analytics for Social Media – October 2010

25. STARBUCK BUZZ CREATED Campaign Period Hyper Analytics for Social Media – October 2010

26. TOYOTA RECALL SENTIMENT ANALYSIS Overwhelming negative mainstream media coverage and very little negative social media comment Hyper Analytics for Social Media – October 2010

27. We analyze 18 months of historical data and live streams in real time We use a special algorithm and then have real people improving the result up to 95% accuracy. 95% accuracy Vs 70-80% automation alone US AIRLINE INDUSTRY STUDY JUNE 2009 Hyper Analytics for Social Media – October 2010

30. SUPER BOWL Correlation of Tweets and Ads Hyper Analytics for Social Media – October 2010

31. SUPER BOWL By Volume Mullen and Radian6 O’Reilly and PeopleBrowsr O’Reilly and PeopleBrowsr By Volume By Positive Hyper Analytics for Social Media – October 2010

32. 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 everyday Velocity 10,000 Mentions/day filtered to 180 Meaningful comments Hyper Analytics for Social Media – October 2010

33. TWEETS PER CAPITA Source: PeopleBrowsr DataMine A new SocioEconomic KPI Hyper Analytics for Social Media – October 2010

34. THE NEXT TWO YEARS The Conversation Stream becomes the Conversation Cloud A real time historical record Hyper Analytics for Social Media – October 2010

35. THE NEXT TWO YEARS The Conversation Cloud becomes the Rich Metadata Cloud Social Media Stream will become the core backbone for people data Hyper Analytics for Social Media – October 2010

36. CUSTOM ANALYTICS Hyper Analytics for Social Media – October 2010

37. SENTIMENT ANALYSIS Hyper Analytics for Social Media – October 2010

38. SENTIMENT ANALYSIS BY DAY Hyper Analytics for Social Media – October 2010

39. SAMPLE POSITIVE TWEETS Hyper Analytics for Social Media – October 2010

40. SAMPLE NEGATIVE TWEETS Hyper Analytics for Social Media – October 2010

41. VOLUME OF MENTIONS Hyper Analytics for Social Media – October 2010

42. REACH Hyper Analytics for Social Media – October 2010

43. WORD CLOUD Hyper Analytics for Social Media – October 2010

44. TIME TARGETING Hyper Analytics for Social Media – October 2010

45. GEO TARGETING Hyper Analytics for Social Media – October 2010

46. GEO TARGETING Hyper Analytics for Social Media – October 2010

47. AUDIENCE PROFILING Hyper Analytics for Social Media – October 2010

48. AUDIENCE PROFILING Hyper Analytics for Social Media – October 2010

49. BLOGWORLD ANALYTICS PLATFORM http://Analytic.ly/Blogworld Hyper Analytics for Social Media – October 2010

50. EXPERIMENTAL APPS RESEARCH.LY What can we build? RESEARCH.LY Contextual Search and Post Inline Content RESEARCH.LY HyperLocal Linked to other netwoks Hyper Analytics for Social Media – October 2010

51. Hyper Analytics for Social Media – October 2010 SEARCH THE WORLD OR JUST THE COUNTRY OR CITY YOU WANT The first thing you will notice are the Country and City drop down menus Use these as you search, so the results you get are more relevant t2.ly uses the geo metadata in Tweets

52. Hyper Analytics for Social Media – October 2010 SEARCH EVERY TOPIC OR JUST THE ONE YOU LIKE Refine the search for Your Community Choose any Topic that is more interesting and relevant to you

53. Hyper Analytics for Social Media – October 2010 CUSTOM URL FOR DIRECT SEARCH Define your search directly from the URL Select Location, Category and Keyword and start browsing!

54. Hyper Analytics for Social Media – October 2010 TWO WAYS TO START SEARCHING Click on any of the words in the ‘Most Retweeted’ box to start searching Start typing a Tweet in the ‘Compose a Tweet’ box. Click any word you type to start searching on that word to show related results OR

55. Hyper Analytics for Social Media – October 2010 RECURSIVE SEARCH Now t2.ly comes to life; a Twitter stream with related, relevant Tweets appears below Click on any word in the Search Stream to continue drilling down for refined results

56. Hyper Analytics for Social Media – October 2010 FIND A RELATIONSHIP PATH… Degrees of separation (1º, 2º, 3º and 4º) show how many ‘steps’ you are from the original Tweeter The power of demonstrating this connectedness is of enormous benefit in creating trust and value within the search results

57. Hyper Analytics for Social Media – October 2010 WHO KNOWS WHO KNOWS YOU… 1º - you follow them 2º - you follow someone, who follows them 3º - you follow someone, who follows someone, who follows them 4º - you follow someone, who follows someone, who follows someone, who follows them

58. Hyper Analytics for Social Media – October 2010 SEARCH IN FRIENDS STREAM Find all your friends who Tweeted about any search keyword Choose to filter the stream by gender or sentiment

59. Hyper Analytics for Social Media – October 2010 RICH MEDIA These are currently related and trending pictures you can use in your Tweet These are currently related and trending @Names, Hashtags, URLs you can use in your Tweet These are the analytics of your chosen keyword

60. Hyper Analytics for Social Media – October 2010 RELATEDNESS & CONNECTEDNESS Every search also shows related and connected data in the form of images, videos, @names, #tags, retweets and URLs Each result can be used to search deeper just by clicking it or used as content for your own tweet in the Compose box

61. VAST DYNAMIC DATA STORES POWER COLLECTIVE CONSCIOUSNESS Hyper Analytics for Social Media – October 2010

62. REFERENCES This Deck http://slidesha.re/HyperAnalytics www.Analytic.ly Socialnomics09 Social Media in Plain English PeopleBrowsr Super Bowl Study PeopleBrowsr Top 20 Brands Study www.ReSearch.ly 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/ Hyper Analytics for Social Media – October 2010 Jodee Rich CEO @PeopleBrowsr @WingDude Joe Fernandez CEO @JoeFernandez @Klout