Highlights opportunity to process and analyse big data sets from social psychological data

1. suresh "frequent reader"
GreatMystery14
Suresh S.
soody
soody
www.facebook.com/sureshsood
ssood
Hero5!
twitter.com/soody
www.bravenewtalent.com/talent/suresh_sood
www.linkedin.com/in/sureshsood scuzzy55
Geektoid Mangala
suresh.sood@uts.edu.au
http://www.slideshare.net/ssood/patterns

2. Agenda – Social Big Data
1. What’s this all about – Big Data ?
2. What does big data mean for business and consulting ?
3. Accessing and processing big data
4. Big Data Case Studies:
– Social media brand stories (PhD research)
– Australian Twitter Analysis (Commercialisation)
– Sydney International Airport (Consulting)
5. Predictions from Big Data
6. Tools and Visualisation of Big Data
7. Where are the new jobs?

3. 3

4. 4
MX , 19 July 2011

6. What is Big Data ?
Unknown relationships
Unstructured data
95% of data not collected
Social-Psychological- local-Mobile-GPS-M2M
6

7. Social CRM integrates social (psychological) data
7

8. Variables and Data Types in Big Data Set
Aquarius,Aries,Cancer,Capricorn,Gemini,Leo,Libra,
Pisces, Sagittarius,Scorpio,Taurus,Virgo
An-Verb,An-Vis,Hol-Verb,Hol-Vis
A&F,Beijing ,Gucci,LVMH,New York,Old Navy,
,Paris, Sydney, Tiffany, Tokyo, Tommy, Versace
Depriv/Enhance,Enhance/Depriv
Africa,Argentina,Australia,Australia/Hong
Kong, Austria, California, Canada, China, Egypt, Engla
nd, Finland, France
Germany, Guernsey, Holland, India, Indonesia, Ireland
, Israel, Italy Ambivalent, Employee, Opposer, Reporter, Supporter
, Japan, Kuwait, Malaysia, Nepal,Paraguay 11. Committed Partnerships, 12. Compartmentalised
, Philippines, Phillipines, Portugual, Saudi Friendship,13. Childhood friendship,14. Courtship,15. Fling, 16.
Arabia, Singapore South Secret-Affair, 17. Enslavement , 2. Marriages of Convenience,3.
Africa, Spain, Sweden, Taiwan, Thailand,UK ,USA Best Friendships,4. Kinships, 5. Rebounds/ Avoidance-Driven,6.
Courtships,7.Dependencies 8. Enmities, 9. Love-Hate (Sweeney and
Chew)

9. 9

10. Exploring Variable Distributions (Training Data Set)

11. Data Visualisation of Variables (Training Data Set)

12. Item Frequency In Support of Association Rules

13. Display of Decision Tree for Brand as Target Variable

14. Model Comparison By Variables/Predictors

15. 15/10

16. Why Revolution R ?
1.SAS Data Access with the ability to import SAS files directly into R, without the
need for a separate SAS license.
2.Modern Editing and Debugging for R: Includes a complete IDE for the R language
with a syntax-aware script editor for highlighting, indentation, and more. A full-
featured visual debugger provides one-click breakpoints and step processing to
improve code quality and the productivity of every R programmer.
3. Revolution R Enterprise is compatible with all 2,500+ open-source packages
developed by the R community. Key community packages come pre-installed
4. Multi-processor performance. Revolution R Enterprise uses the power of
multiple processors to run common matrix calculations in a fraction of the time.
5.Access Big Data: Revolution R breaks through R’s memory barrier out-of-memory
data store that supports Big Data: data sets with thousands of variables and
millions of rows. Easily process and select smaller aggregates from this data store
using R commands, instantly making Big Data accessible to all of R’s thousands of
in-memory analytics and data visualization functions
16/10

17. Why Revolution R ?
6.Analyze Big Data, Fast: Revolution R Enterprise enables statistical analysis of Big Data
at unparalleled speed. Perform cross-tabulations, linear regressions and logistic
regressions without the need for sampling or expensive specialized hardware. A high-
performance out-of-memory data storage format combined with parallel streaming
algorithms makes statistical analysis in Revolution R Enterprise many times faster than
those of well-known legacy
7.A Stable R Distribution for Single Users and Teams: Built on the latest stable
distribution of R and subjected to a rigorous build and test process, Supported on 64-
bit Red Hat Enterprise Linux 5 and 32-bit and 64-bit Windows systems
8. Integrate R into User Applications. RevoDeployR, a server-based platform for
Revolution R Enterprise, makes R ready for enterprise deployment. A scalable Web
Services API makes it easy for application developers to securely integrate results
computed in R into BI dashboards, spreadsheets, custom web applications and more.
9.Support and Services
10. Roadmap an easy-to-use graphical user interface, more statistical algorithms for Big
Data, additional support for computing on local grids and in the cloud, integration with
enterprise data stores including Hadoop.
17/10

18. …Blogs are like conversations with friends. You share what you feel
and what excites you about certain things. It's almost as good as
being there. The fact that others can Google your topic and read is
like tuning into a television station.
We all want to know what's out there. Who's doing
what, shopping where and what products help others. Blogs are
just another way to share all the great things, not so great things
and just a part of who we are. An outlet if you will. The blogisphere
community is all connect and we make contacts in many ways.
Through posts, through twitter conversations, through smaller nit
community's, live web casts, and through conferences that we met
in person. We make many friends and help each other with lot of
topics. Many of us are Mom bloggers who stay at home and have
no way of making new friends or communicating with others until
we found blogging. Blogging creates friendships and that's what
makes us real and connected.
40 year old Mom blogger “nightowlmama” (#260)18

19. Theory and Research on Consumers’ Reports of Interactions with Brands and Experiencing Primal Forces, Suresh
Sood, 2010
19

20. “…According to the spreading activation
model of Collins and Loftus (1975), the
concepts (or brands in this case) are
represented in memory as nodes…”
“Most of what we know we don’t know we know. It usually seems that we
consciously will our actions, but this is an illusion” (Wenger, Daniel 2002)
20

21. Adly Influencers via Twitter
Reach(millions) Influencer
10 savvy/active moms Jenny McCarthy, Kourtney Kardashian, Tori Spelling
6 passionate sports fans Cristiano Renaldo, Paul Pierce, Nick Swisher
12 trend conscious teens Paris Hilton, Kim Kardashian, Lauren Conrad
16 teen males 50 Cent, Ryan Sheckler, Ryan Higa.
14 women 18-34 Ivanka Trump, Mandy Moore, Serena Williams
20 men 18-34 Mark Cuban, Jalen Rose, Michael Ian Black

22. Twitter and Marketing Predictions
• Tweets is “found data” without asking questions
• More meaning than typical search engine query
•
• Large numbers of passive participants in natural settings
• Twitter can predict the stock market (Lisa Grossman, Wired, Oct 19 2010)
• Predict movie success in first few weekends of release
– “…it also raises an interesting new question for advertisers and marketing
executives. Can they change the demand for their film, product or service buy
directly influencing the rate at which people tweet about it? In other words,
can they change the future that tweeters predict?”
Tech Review, http://www.technologyreview.com/blog/arxiv/25000/
22

23. Google Flu Trends

25. When does Aus/NZ Tweet?
Count of Tweets
Hour of Day

26. When is Aus/NZ Most Happy?
Proportion of Tweets with
+ve emotion
Hour of Day

27. Which City Swears Most?
Proportion of Tweets with
profanity
City

28. Which City is Sad ?
Proportion of Tweets with
sadness
City

29. Which Archetype ?
Proportion of Tweets with
archetype
count of tweets

30. 2011 Australian Social Media Data
Mobile internet 50% penetration amongst online
Australians in 2010
35 % penetration of smartphones among online
Australians
8% of online Australians use tablet
[ end 2011 forecast 24% +]
71% accessing audio or video content online in 2010 and
35% on a weekly basis
3 in 4 online Australians tap consumer opinion about
brands, products and organisations, found in social media
63% have Facebook profile
46% have clicked the Facebook ‘Like’ button for a
brand, product, org.
43% share their opinions about brands and products via
social media
53% engaged with a brand or company on a social
networking site
36% engaged with government or politicians on a social
networking site
Source: Burson-Marsteller Asia-Pacific Source: Nielsen
Social Media #Infographics H1 2011 State of the online market: evolution or revolution?
August 2011 March 2011 30

31. Australian Facebook Demographics (Source:socialbakers.com)
31

32. March 2011 “Online Australians Shift To Social Networks”
Most Online Australian Adults Use Social Media Regularly
Increasing social
media engagement
32

33. January 2012 “Global Social Media Adoption In 2011”
Countries Show Distinct Social Media Behaviors

34. January 2012 “Global Social Media Adoption In 2011”
Countries Show Distinct Social Media Behaviors (Cont.)

35. January 2012 “Global Social Media Adoption In 2011”
Countries Show Distinct Social Media Behaviors (Cont.)

36. Popular Social Networking Sites by Country
China (420 M) - QQ, Xiaonei (now RenRen), 51, Tencent
UK - Facebook, Bebo, MySpace
NZ - Facebook, Bebo MySpace
USA - Facebook, MySpace, Twitter
Korea – Cyworld
Japan – Twitter, Mixi.jp (22 M users at 31/10)
Germany - Facebook, StudiVZ, MySpace
These social networks exclude popular dating sites
e.g. Flirtomatic (UK) and loveonline (NZ)
36

38. Google+ Stream and Hangouts
38

39. New Generation of Social Platforms
39

40. Tag Cloud of Paige’s Story About Travel to Paris
Created from Daniel Steinbock’s TagCrowd under Creative Commons ©
4040

41. Elaboration of Trip to Paris Blog Story (Means-End & Heider)
Woodside, Sood & Miller 2008 When Consumers and Brands Talk Psychology & Marketing
18."We went on Fat
17. "I wanted Paige to get a feel Tire's day trip to
+ 19....."I know Paige will
for shopping experiences that Monet's gardens and treasure the memory of
she would not have at home (aka house in Giverny, about this girl's trip for many
the ubiquitous mall). " 16. "On our trip to Giverny, we met a young an hour outside Paris."+ years to come."
woman from Brisbane, Australia who was
traveling on her own and we invited her to join
us. Three of us enjoyed delicious and
innovative soufflés, while Paige had the rack of
3. Paris
lamb. We shared two dessert soufflés, one 11.Sites
+ chocolate and the other cherry/almond. Yum" •The Marais
•Notre Dame
•L'Arc de Triomphe - 248 steps up and 248 steps
+ down...
1.Gayle 15." Michael Osman is an American artists •Champs Elysee
living in Paris." •Jacquemart Museum
"He supplements his income by being a •Louvre Lite
+ tour guide." I" found out about him on
Fodors"
•Musee D'Orsay
•Les Invalides, Napoleon's Tomb and the
2. Paige "So I engaged Michael for two days." Napoleon Museum
•Sacre Coeur
•Monmartre
+ 14. "They had decide to come to Paris •Rodin Museum
to find the Harley Davidson store so •Pompidou Museum
they could buy Harley Paris t-shirts." •Train to Vernon, bike to Giverny with Fat Tire
4.”The occasion
Bike Tours
was my cousin 5. “I am a Canadian
•http://www.fattirebiketoursparis.com/
Paige’s 16th” and get by in
13."The father stretched out his cupped •Eiffel Tower
French.”
hands which held all of the pieces they were
able to recover, including the memory stick
and he very solemnly said, "El muerto...".
6. "All I can say is WOW! We rented a 2 9. "I bought a Paris Pratique pocket-sized book at a
bedroom, 1 ½ bath apartment (two 12. Unforgettable Memories Metro station. This handy guide has detailed maps
showers), "Merlot" from ParisPerfect "This trip had so many memories, but here are a few choice of each arrondisement, as well as the metro lines,
http://www.parisperfect.com/ and boy was highlights........On our very first night, knowing that the Eiffel the bus lines, the RER and the SCNF (trains). I'll
it ever perfect! " Tower light show started at 10:00 p.m.... she [Paige] dropped never be without this again."
her camera…down 6 flights…we were stunned…Spanish
Family below standing below *with pieces of the camera+”
7. “We had a full view of the Eiffel from 10."Six months before our trip, I gave
our charming little terrace. ....We were 8. "We were walkable to many good Paige a couple of good guide books on
within walking distance to two metro bistros, cafes and bakeries and only a Paris and suggested she let me know
stops (Pont d'Alma or Ecole Militaire) " few blocks from the wonderful market what her interests were since after all, 41
street Rue Cler." this was to be her trip."

42. Linguistic Inquiry and Word Count (LIWC)
Text Analysis : The Psychological Power of Words
LWIC dimension “I love Paris” Personal texts Formal texts
Paige’s Story
Self-references 6.12 11.4 4.2
(I, me, my)
Social words 10.55 9.5 8.0
Positive emotions 3.04 2.7 2.6
Negative emotions 0.54 2.6 1.6
Overall cognitive words 4.12 7.8 5.4
Articles (a, an, the) 7.74 5.0 7.2
Big words (> 6 letters) 18.40 13.1 19.6
Pennebaker, J. W., Francis ME, Booth RJ. (2001). Linguistic Inquiry and Word Count (LIWC):
LIWC2001. Mahwah: Lawrence Erlbaum Associates.
42

43. 43

44. 44

45. Iconic Sites & Scenes from Paris Blog
• Eiffel tour night show
• The Marais
• Notre Dame
• L'Arc de Triomphe - 248 steps up and 248 steps down...
• Champs Elysee
• Jacquemart Museum
• Louvre Lite
• Musee D'Orsay
• Les Invalides, Napoleon's Tomb and the Napoleon Museum
• Sacre Coeur
• Monmartre
• Rodin Museum
• Pompidou Museum
• Train to Vernon, bike to Giverny with Fat Tire Bike Tours
www.fattirebiketoursparis.com/
45

46. Marketing & Advertising Strategy Implications the Story of Paige
• Story told in natural city setting
• Assume Paris = brand
• Brand is supporting actor enabling Gayle to achieve her goals of
showing Paris to Paige (conscious) and help her coming of age
(unconscious)
• Builds favorable consumer brand relationship:
best friendship (Fournier 1998)
• Show someone Paris:
Share experience,teacher-student,”fairy-godmother” or be the
tourist guide
• Use social relationships to sell cities
• Interpersonal relationships (people travel with people)
• Near conversational interaction with brand:
story is called “I love Paris”
46

47. How Social Media Supports the Myth of Paris
Casablanca
“We'll Always Have Paris”
Lamps, Eiffel Tower,france, City of love , city of
night, street, notredame, lights, landmarks , museums &
bw, church, architecture, galleries, Cafés, coffee, conver
toureiffel, city, cathedral,
sations, friendship, artists, lov
louvre, museum
ers, philosophers
47

48. Brand Equity - Conversational
Conversation Gap - Vacation and Paris Conversation Gap (Rubel 2005)
Brand share of the online conversation
Gap between the total number of
conversations about a category and the
proportion which mention the brand operating
in the category
* Total identified blogs: 99,181,005 @ 18 December, 2008
Paris – Equity Share Analysis of Attributes
Equities of a Brand (Stein 2006)
Topics being mentioned in conversations about
a brand with equity share corresponding to the
frequency at which each topic is mentioned
See pp 115-116 Cook, N 2008. Enterprise 2.0
Hampshire,England: Gower Publishing
* Total identified blogs: 151,048,780 @ 24 November, 2010 48

49. Blog Mentions Sydney Opera House, TaJ Mahal &
Great Wall China
A review of the blogosphere on 8 June 2010 reveals 126.87 million blogs

51. Buzz Campaign Brief Deliverables:
• Social media campaign (micro blogging) igniting conversations around recently launched SSP
restaurants/units/offering
• Customer education via social media around the $500m facelift at Sydney International Airport.
• Social media ‘micro-test’ targeting English speakers over 4 months concluding January 31,
2011.
• Create conversational sparks (social articles) stimulating discussions and interactions around the
four KPIs of SSP Australia
– Environment, Emotional Experience, Service and Product.

52. Service Environment
Blogs - 13 Blogs-27
Videos - 24 Videos-36
Photos - 51 Photos-94
Newsletters-3
Emotion/Experience Product
Blogs-26 Blogs-32
Videos-34 Videos-35
Photos-128 Photos-69
Newsletters-2 Newsletters-3

53. Consumers use social media to
give SSP real time feedback.
• Proof of Concept: Meet Michael H from
Perth, WA. He was a real unsolicited spontaneous
‘Mystery Shopper’ at Trattoria Prego, his
feedback he syndicated to multiple social touch
networks.
•
Confidential | Do not reproduce without prior written permission from MMG

54. Social Network & Media Asset Register
 34 videos
 98 images  2,239 views
 31 videos  4,980 channel views*
 28 comments
 132 Unique photos  14,624 Following
 43 Videos  14,335 Followers
 44 Blog Posts  32,512 Tweets
 146 Lists**
 648 Check-In
 58 photos
 182 Unique Visitors
2,368 views
*number of times more that anyone has looked at YouTube/Freshonthego channel
**incidences where a Twitter users has classified you as important in a unique way - a sign of deeper engagement
Confidential | Do not reproduce without prior written permission from MMG

55. Social articles attract quality
clicks.
These results above are from the past seven days to 31st January 2011 from Bitly.com a
website which follows and tracks all unique links leading back to a specific URL.
Total number of clicks on Bit.ly links over the past four months is 3,499
43% of these links were clicked on from within Australia.
Confidential | Do not reproduce without prior written permission from MMG

56. Facebook Fan Page Socialgraphics
 There are currently 1,263 fans for the SSP Australia
Facebook Fan Page. In comparison, Caviar House &
Prunier (global fan page) has 376 fans and Itacho Sushi
have 642 fans.
 There have been 20,817 views of the Facebook Fan
Page within the last 30 days.
The most frequent referrer to the Facebook Fan Page
from an external source is from YouTube.
There are 31 videos currently uploaded to the
Facebook Fan Page.
 There are currently 15 photo albums uploaded to the
page.
Confidential | Do not reproduce without prior written permission from MMG

57. FreshOnTheGo Key Insights
Right Platform for Target Audience
•FOCUS AREA: Consumer Engagement
Behaviour Analysis: (Campaign highlights)
-
1.Emotional Experience/Environment Lunch With A TSFs - Travel Social Fans
Lingerie Model (Montreux Jazz Café)
http://youtu.be/ky7ea_c-dP8 566 views, 3 tweets, shared to
Facebook 5 times. (.01% engagement - entertaining but not
compelling.)
2. Service/Corporate Culture: Experience Accidental Magic
(SSP) – 165 views http://youtu.be/9HGAy77DJm4 shared to Twitter
130 times, shared to Facebook 10 times. (84% of viewers shared -
STICKY)
:
3.Product Happy Bites at Itacho
http://youtu.be/D98TWCPchRc viewed 224, tweeted 199 times,
shared to Facebook 15 times. (95% of viewers shared - VERY STICKY
CONTENT)
4.Product/Experience/Corporate Culture: That’s Amore
Pizza Making (Prego)-http://youtu.be/9oRq2cnXqrE 172 views, 3
Tweets, shared to Facebook 52 times (31% of viewers shared)
Confidential | Do not reproduce without prior written permission from MMG

58. Key Insights
Confidential | Do not reproduce without prior written permission from MMG

59. Key Insights: Caviar House
The results over past four months indicate Caviar House &
Prunier has 46% greater brand strength since October 2010
39 Unique Pictures
according to *Social Mention.com. 8 Videos
9 Blog Posts
There have been no “offers” in place for Caviar House and
therefore limited “brand play” as there was no basis for 2, 001 Following
 902 Followers
buzz and no interaction between local and global brand  16 Lists
teams.
55 Check-Ins
Text
Text
Caviar House & Prunier video content was the popular and 11 Unique Visitors
the primary source of engagement and more could be done 7 videos
on the education of the Global brand strength and 289 views
localisation of the offer (fresh seafood) in conjunction with 23 Pictures
global social media team of Caviar House. 3 Videos
14 Pictures
624 Views
Confidential | Do not reproduce without prior written permission from MMG

60. Key Insights: Danks Street Depot
195 Check-In
38 Unique Visitors
SocialMention.com indicates a 76% greater brand signal than
when the campaign commenced for search parameter 2,001 following
1 ,284 followers
“Danks Street Depot Airport”.  14 Listed
10 Pictures
Tweets and blogs focusing on Danks Street Depot’s ethos 3 Videos
5 Blog Posts
proved to be the most engaging content and Product the most
common focus articulated in real-time feedback. 16 Pictures
3 Videos
6 videos
242 views
13 Pictures
Confidential | Do not reproduce without prior written permission from MMG

61. Key Insights: Bambini Wine Room 2,001Following
Bambini Wine Room has 74% greater brand strength than 1,178 Followers
campaign commencement. 17 listed
SocialMention.com sentiment analysis shows that compared to 103Check-In
their primary competitor The Black Tonic Espresso
Bar, Bambini Wine Room has a more visible online presence by 17 Pictures
2 Videos
Foursquare check-ins and customers would like to see more 7 Blog Posts
continuity of brand message.
12 Pictures
Environment/Experience,Product was “ notable ” to a 2 Videos
traveler. (see real-time guest feedback by @witheredwords)
4 videos
247 views
11 Pictures
Confidential | Do not reproduce without prior written permission from MMG

62. Key Insights: Itacho Sushi
16 pictures
2 videos
The results over the past four months indicate that
Itacho Sushi has 64% greater brand strength than when 2, 001 Following
1, 060 Followers
the campaign commenced. The sentiment analysis 7 listed
shows that compared to their primary competitor China 26 Unique Pictures
Grand Restaurant, by customer segmentation, Itacho 3 Videos
6 Blog Posts
Sushi has a far more visible brand presence.
48 Check-In
PRODUCT is the most popular KPI focus illustrated by 11 Unique Visitors
measured interaction - 98% “Last Mile” share rate
reported on YouTube. Immediate next steps include 5 videos
317 views
development of contextually relevant videos in Asian
languages, as Chinese flights to Australia have since 13 Pictures
2009, increased by 26.2%. 1, 744 views
Confidential | Do not reproduce without prior written permission from MMG

63. Key Insights: Montreux Jazz
Cafe
SocialMention.com indicates 60% greater brand strength since
1 439 Following
889 Followers
October 2010. Competitive analysis indicates greater online 8 listed
presence than The Terrace Bar by check-in and mention. 18 pictures
2 videos
Montreux Jazz Café’s online presence has lead to more frequent
31 Unique Pictures
engagement and mention from local key influencer audiences. 25 Videos (including 19 videos from
the Montreux Jazz Festival)
11 Blog Posts
Focus feedback included Product, Emotional Experiences and 178 Check-In
26 Unique Visitors
Summer of Lunch campaign demonstrated an integrated social
approach with customers going “ Last Mile ” when
6 videos
@montreuxjazzsyd online friends met in real life with purpose and 816 views
drove sales revenue.
Montreux Jazz Cafe is the first of SSP Australia to demonstrate 10 Pictures
characteristics of a community.
Confidential | Do not reproduce without prior written permission from MMG

64. Key Insights: Prego
13 pictures
1 videos
2 001Following
Trattoria Prego (a ‘made up’ brand) has 74% increase in brand 854 Followers
strength since October 2010 according to SocialMention.com. 11 listed
 9 Unique Pictures
Trattoria Prego is one of the most engaged social brands of SSP with 2 Videos
6 Blog Posts
redemption of “FreshonTheGo” offers which increased top-line
sales. 69 Check-In
Text 16 Unique Visitors
Text Environment
Focus feedback on Product, Emotional Experience Text
and
3 videos
have been articulated in real-time feedback and through multiple social 325 views
platforms by engaged customer as well crisis management program
tested/deployed as necessary for complaints. 8 Pictures
Confidential | Do not reproduce without prior written permission from MMG

65. Twitter Town Hall @ White House
• 6 July 2011
• #AskObama
• 160,000 questions and comments combine into 17 questions
• Multi prong approach to narrow Tweets :
– Partner with service provider Mass Relevance to curate, visualize and integrate
which topics were generating the greatest discussion.
– Curation technology TweetRiver aggregates and filters Tweets with the #AskObama
hashtag into real-time topic streams, including jobs, the budget, taxes, education
and health care.
– Use own signals to measure engagement (Retweets, Favorites and @Replies)
within these topics.
– Group of Twitter users (called "curators") helped flag questions from their
communities through retweets
https://dev.twitter.com/blog/behind-scenes-white-house

66. ns for “Twitter Town Hall”,
arackobama (graph 2).
event, the terms monitored included Summary Twitter Town Hall @ the White House
tions for “Twitter Town Hall”, monitor the economic focus event, the terms monitored included
To
@barackobama (graph 2). #AskObama (graph 1) and mentions for “Twitter Town Hall”,
@whitehouse, @townhall and @barackobama (graph 2).
#AskObama
and “Twitter Town Hall” The Town Hall event on July 6th
Jul 04 Jul 05 Jul 06 Jul 07 Jul 08 between 2-3pm ET was almost
200,000 equal to that of the 5 day long
pre-buzz period from June 30th –
150,000
July 5th.
100,000
50,000
The Town Hall event on July 6th
3 Jul 04 Jul 05 Jul 06 Jul 07 Jul 08 between 2-3pm ET was almost
0
The day of the event, July 6th , long
equal to that of the 5 day The Town Hall
Jun 30 Jul 01 Jul 02 had nearly 3 Jul period from June Jul 06
pre-buzz 04 as many
Jul 03 times Jul 05 30th – Jul 07 Jul 08 between 2-3pm
July 5 th.
#AskObama Town Hall equal to that of
mentions as compared to the pre-buzz period
pre-analysis and Twitter Town July 5th.
Hall.
The day of the event, July 6th ,
had nearly 3 times as many
Jul 04 @whitehouse 06
Jul 05 Jul Jul 07 Jul 08 #AskObama Town Hall
@townhall Most Retweeted Usernames: to the
mentions as compared The day of the
@barackobama @barackobama, @whitehouse, Town
pre-analysis and Twitter had nearly 3 tim
@townhall, @mashable
Hall. #AskObama To
20,000
mentions as com
15,000
pre-analysis an
03 Jul 04 Jul 0510,000 06
Jul Jul 07 Jul 08 Hall.
male 68,534: 58.1%
5,000 Most Retweeted Usernames:
0 @barackobama, @whitehouse,
9,382: 41.8%
Jun 30 Jul 01 Jul 02 @townhall, @mashable
Jul 03 Jul 04 Jul 05 Jul 06 Jul 07 Jul 08
Most Retweeted
@barackobama
male 68,534: 58.1%
@townhall, @m
Salesforce radian6 report
34
ale 49,382: 41.8%

67. Gender: Twitter Town Hall @ the White House
Salesforce radian6 report

68. e day of the event, July 6th, 2011, the Financial Security segment grew to be the major
of the pie with over 54.4%, an increase of 20.8%
Total View – Issue Segments and Gender Breakdown for 6 July 2011
National Protection
6,950: 18.6%
Financial Security
20,291: 54.4%
Total View
July 6th, 2011 SEGMENT OVERVIEW
Development
4,767: 12.7%
Within each of the segments we can also take a look at
the gender breakdown for each identified topic.
Wellness
5,260: 14.1%
100.00%
90.00%
80.00%
Twitter
70.00% Town Hall @ the White House Salesforce Radian6 Report 4
60.00%
50.00%
40.00%
30.00%
20.00% Male
10.00%
Female
0.00%
Salesforce radian6 report

69. Sharing Stories
What happens when you tell stories? Two magical things: You build trust
with other people in your network, and from there you build
empathy…is when you share the emotions that other people have and
express. It’s a powerful, deeply primal experience.
ShareThis! Deanna Zandt, Berrett-Koehler Publishers, 2010
69

70. Sponsored Stories- Facebook
70

71. Stories and Listening to Brand Attributes
• Your own stories are ego centric
• Stories others tell about you to friends and associates
(future prospects) are powerful
– What vocabulary do others use
– What do others tell about your skills
– What stories do you tell about others
• Brand attributes are what others write and repeat
71

72. Social Media Conversation Calendar Triggers
• Tweets ~ 1 to 2 per day
• Facebook status daily
• YouTube weekly
• New content ~ 3 to 5 hours per month
• New online contacts ~ 1 hour per month
• New blog post ~ 1 per working day
72

73. Analytics from Social Big Data
8 Levels of Analytics Key Social Media Questions
(Davenport)
Standard Reports What conversations are taking place?
Ad Hoc reports When and where are conversations taking place?
Query Drilldown What are the sentiment of conversations?
Alerts What actions are required?
Statistical Analysis Why are these conversations occurring?
Forecasting What if conversations continue?
Predictive Modeling What conversations are next?
Optimization How can we lead conversations?
http://manobyte.com/blog/index.php/2008/11/what-is-social-media-analytics
orginally adapted from Davenport T (2007), Competing on Analytics
73

74. First Step Monitoring [Brand] Conversations & Tips
• Social Media Dashboard
– All social media sources relating to brand
– RSS technologies
– Mashups (e.g. YouTube, Flickr, Twitter, Nielsen, Google )
• Weak Signals
– Twitter early warning in advance of blogging
• Set up comprehensive Google Alerts
• Set up a feed reader with relevant blogs and new feeds
• Use Twitter Search to follow hashtags and keywords in Twitter streams
• Start immediately (~3 mins) with Netvibes and vocabulary
74

75. Google Reader
• Free
• Collects info from Twitter, blogs, and other RSS sources
• Allows for easy sharing
• Info all in one spot
• Less real-time (both benefit and drawback)
• Track what’s read/not
• Powerful: Star, share, email, tag, notes, trends
• LinkedIn - Job changes, New connections, Updates and Groups
75

76. Other monitoring options
76

77. A New Way of Marketing ?
Social Network
Marketing
1:1 ‘All Customers
Marketing in a network
interrelated’
Segment ‘All Customers are
Marketing different’
‘All Customers
Shotgun in a segment
Marketing the same’
‘All Customers
the same’
77

78. Facebook Social Graph
78

79. Facebook Object Types for Social Graph
Activities Businesses Groups Organizations People Places Products and
Entertainment
Activity Bar Cause Band Actor City Album
Sport Company Sports_league Government Athlete Country Book
Cafe Sports_team Non_profit Director Landmark Drink
Hotel School Musician State_province Food
Restaurant University Politician Game
Public_figure Product
Song
Movie
Tv_show
Websites UPC/ISBN Other latitude
longitude Contact Info :
Blog UPC code Other street-address
location locality email
Website ISBN number region phone_number
postal-code fax_number
Article
country-name
79

80. Giant Global Graph
I'll be thinking in the graph.
The ABC as Social Graph
My flights. Topics Events
My friends.
Things in my life. Music Programmes
My breakfast.
What was that? Oh, yogurt, granola, nuts, and fresh fruit, since you ask.
Users Gardening
Submitted by timbl on Wed, 2007-11-21
http://dig.csail.mit.edu/breadcrumbs/node/215 News Food
Facebook Social Graph
80

81. Social Network Representation
• Primary focus is actors & relationships # actors & attributes
• Nodes (Actors) connected by Links (Ties/relationship or edge)
Adjacency list
• Links represent flows or transfer
– material goods or information 1 1: 2
Graph or 2: 1, 3
sociogram
2 3: 2
3
Adjacency matrix
1 2 3
Actors 1 0 1 0 Relationship
2 1 0 1 1 = presence of link
3 0 1 0 0 = no direct link
81

82. 82

83. NodeXL - Excel 2007 template for viewing and analyzing network graphs
www.codeplex.com/NodeXL 83

85. Key Network Measures Diana’s
Clique
krackkite.##h (modified labels)
• Degree Centrality
• Betweenness Centrality
• Closeness Centrality
• Eigenvector Centrality
Connector
(hub)
Contractor ? Vendor
Broker
Boundary spanners
85

86. Facebook EdgeRank
• Object = status update or post
• Edge = like, comment or interaction with object
• Interesting info  more people interactions resulting in higher rank and story in “Top News”
• Posting status updates without conversation does not get high rank and move into “Top News” feed
• EdgeRank is based on sum of three factors:
– affinity or the relationship between the creator and user
– interaction with the object (likes, comments have different levels of user engagement)
– timeliness means new objects have better chance
• 6 Tips to increase EdgeRank
– Publish objects that encourage interaction
– Create a forum
– Make most of photos and videos
– Share links
– Keep it fresh
– Ask users to share
Source: 6 Tips to Increase Your Facebook EdgeRank and Exposure by Jim Lodico, 28/4/2011
86

87. LinkedIn
• Over 120 million users
– 26m+ members in Europe
– 6m+ members in the UK
– 2m+ members in France
– 2m+ members in the Netherlands
– 2m+ members in Italy
– 1m+ members in the DACH region (Germany, Austria and Switzerland)
– 1m+ members in Spain
– 10m+ members in India
– 4m+ members in Canada
– 4m+ members in Brazil
– 2m+ members in Australia
• 2M+ professionals in Australia (~40% + of professionals)
• Widely used in Financial Services (Sydney, Brisbane & Melbourne)
• Australian member usage
~ 8 minutes per month
• 6.5 million students and 9 million recent college graduates
• More than 2 million companies have LinkedIn Company Pages. affluent & influential membership.
87

88. LVMH – Louis Vuitton
88

89. Blendtech
12,860,143
Susan Boyle “United Breaks Guitars”
79,804,980 10,177,221
Old Spice
The Man Your Man
Could Smell Like
37,180,978
** views current as at 19 November 2011 89

90. YouTube Insight – Video Analytics
90

91. Where will the jobs come from?
1. Data scientist for big data insights? (Business/IT)
2. Big Data compliments all organisation wide data
3. Big data not owned by marketing, business or IT
4. Requirement to take real time data and circulate across an
entire enterprise?
5. Who is responsible ?
6. Reporting structure?
7. Do we need a new organisation or team?
8. Is this about organisational change?
9. Social media or Big data Centre of Excellence
10. What happens if opportunities exist from the data insights?

92. Caution!
“Children never put off till
tomorrow what will keep
them from going to bed
tonight”
ADVERTISING AGE
92