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The Future of Social
Media Research!
Or how to re-invent social media
monitoring in 10 steps




Francesco D’Orazio
@abc3d...
legacy!
Since it emerged 15 years ago, the industry has been
largely responsible for driving some of the most
interesting ...
qual/quant!
blurring!
This is an approach that for the first time enables both a
granular and a birds-eye view of the data,...
a new
epistemology !
And with computation also comes the ability to mine
larger (and messier) datasets, which is in turn s...
Social media monitoring is a growing industry but
one that is stuck in its old ways. And in need a of a
urgent re-think. O...
the 480+ smm
platforms are
broken!
Add to this the more systemic revolutions the
industry is facing, such as the visualization of social
media, which is goin...
#tumblr: !
85m post / day!
84% images !
social media
research is not
web analytics!
It’s not
quantitative
data!
It’s qualitative
data on a
quantitative
scale!
Drop the
‘media’. !
It’s ‘social
media data’!
It needs social
science not
‘media
monitoring’!
How can 

social research 

fix smm 

in 10 steps!
1!sampling
beyond
keywords!
Great	
  Britain	
  
Indonesia	
  
USA	
  
Malaysia	
  

09	
  am	
  

Nigeria	
  
Ireland	
  
India	
  
Spain	
  
France	...
4	
  maps	
  by	
  visibility	
  
4	
  maps	
  by	
  visibility	
  
Mentions of brand x!

@Brand follower activity!

0.1%!
Decoding your online audience
Discovering clusters of fans using Social
Network Analysis
"
Detecting social communities in "
Question Time’s Twitter audience
NHAparty!

WillBlackWriter!
RippedOffBriton!

OwenJones84	
  

SalmaYaqoob!

johnprescott	
  

richardcalhoun!

ChrisBryan...
Orange Cluster

41%	
  
59%	
  

- 42 y.o. White British
- Manufacturing professionals, Nurses, Teachers
- From London (48...
2!

from 

content to
context!
© Alexandre Farto aka Vhils 2010

Most Social Media Monitoring
platforms focus on just Content
© Alexandre Farto aka Vhils 2010

But we also wanted to understand
Context and Behaviour
Dimensions of Social Data
Content

Demographics

Social Graph

Interest Graph

Behaviours
Nose-to-tail indexing

or Bigger Big Data


Behaviours	
  

Social	
  Graph	
  

Demographics	
  
Interest	
  Graph	
  

C...
Data anthropology
3!

from 

analytics to
intelligence

frameworks!
AnalyticsIntelligence

How many What time of the week

Tweets/Hour?
 is best for what?


 
How many What’s the brand
negat...
Measuring Visibility
4! down 

break
the social silo!
Predicting the
Oscars

Integrating social data
with multiple external
datasets to increase
predictability
Images
Location

EXP #1
Reality Mining

Call Log
SMS Log
Bluetooth
Accelerometer
Gyroscope
Orientation
Activity
Running Ap...
5! scalable 

human-analysis!
6!machinelearning!
7!
dataUX !
A data canvas
Visual Mining
Data Transparency
8!decisionmaking!
9!

hybrid 

methods!
SOCIAL PANELS > real-time segments

Dynamic
Segments
Real-time Audience
Insights
Pulsar	
  |	
  Social	
  Data	
  Intellig...
A Nation Divided?
A Social Panels case study

50k readers

50k readers

23,000 Tweets

50k readers

22,000 Tweets

50k rea...
A Nation Divided?

How 300,000 readers of six top UK newspapers
are feeling about the death of Margaret Thatcher

Positive...
10!






making
research
programmable

Social	
  Data	
  Intelligence	
  

	
  

	
  

	
  @pulsar_social	
  |	
  PulsarPla]orm.com	
  
Future Social Media Research
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Future Social Media Research

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In an article recently published in Research World Magazine and on his Tumblr blog Abc3d, our Chief Innovation Officer, Francesco D’Orazio outlines the challenges facing the social media monitoring industry – and 10 ways to tackle them.

http://abc3d.tumblr.com/post/62887759854/social-data-intelligence

Published in: Marketing, Technology, Business

Transcript of "Future Social Media Research"

  1. 1. The Future of Social Media Research! Or how to re-invent social media monitoring in 10 steps Francesco D’Orazio @abc3d | PulsarPlatform.com
  2. 2. legacy! Since it emerged 15 years ago, the industry has been largely responsible for driving some of the most interesting evolutions in the research space, such as the democratization of text mining and computational approaches to mining qualitative information.
  3. 3. qual/quant! blurring! This is an approach that for the first time enables both a granular and a birds-eye view of the data, making it possible to produce qualitative observations on a mass scale. A new perspective that is blurring the lines between qualitative and quantitative thinking.
  4. 4. a new epistemology ! And with computation also comes the ability to mine larger (and messier) datasets, which is in turn steadily shifting the focus of what we call knowledge, from understanding causation to identifying correlations.
  5. 5. Social media monitoring is a growing industry but one that is stuck in its old ways. And in need a of a urgent re-think. Or As McLuhan would have put it, we look at social data through the rear view mirror
  6. 6. the 480+ smm platforms are broken!
  7. 7. Add to this the more systemic revolutions the industry is facing, such as the visualization of social media, which is going to pose huge challenges to an industry that’s been entirely built on text mining.
  8. 8. #tumblr: ! 85m post / day! 84% images !
  9. 9. social media research is not web analytics!
  10. 10. It’s not quantitative data!
  11. 11. It’s qualitative data on a quantitative scale!
  12. 12. Drop the ‘media’. ! It’s ‘social media data’!
  13. 13. It needs social science not ‘media monitoring’!
  14. 14. How can 
 social research 
 fix smm 
 in 10 steps!
  15. 15. 1!sampling beyond keywords!
  16. 16. Great  Britain   Indonesia   USA   Malaysia   09  am   Nigeria   Ireland   India   Spain   France   South  Africa   Other   10  am   11  pm   10  pm   9  pm   8  pm   12  pm   11  am   1  pm   2  pm   7  pm   07  May  2013,  10  pm:   the  rumour  spreads   on  Twi?er   6  pm   5  pm   4  pm   3  pm   How fast does news travel? Conversations about Alex Ferguson retirement by the hour by country
  17. 17. 4  maps  by  visibility  
  18. 18. 4  maps  by  visibility  
  19. 19. Mentions of brand x! @Brand follower activity! 0.1%!
  20. 20. Decoding your online audience Discovering clusters of fans using Social Network Analysis
  21. 21. " Detecting social communities in " Question Time’s Twitter audience
  22. 22. NHAparty! WillBlackWriter! RippedOffBriton! OwenJones84   SalmaYaqoob! johnprescott   richardcalhoun! ChrisBryantMP! PennyRed! steveclarkuk! mehdirhasan! davidschneider! fleetstreetfox! paulwaugh! oflynnexpress! RicHolden! bbc5live! BBCNews! afneil! bbcquestiontime  
  23. 23. Orange Cluster 41%   59%   - 42 y.o. White British - Manufacturing professionals, Nurses, Teachers - From London (48%), Manchester (6%), Liverpool (5%) - Jewish, Christian - Into politics, tech news, environment, cooking, tennis; - Following @BBCBreaking, @Ed_Miliband, @Queen_UK. Fuchsia Cluster Green Cluster 37%   63%   - 28 y.o., White British - Students, Musicians and actors - From London (41%), Manchester (10%), Liverpool (4%) - Christian and Jewish - Into partying , reading, comedy, football; - Following @stephenfry, @RealDMitchell and @daraobriain - 32 y.o., White British - Manufacturing professionals, Nurses, Teachers - From London (48%), Manchester (6%), Cardiff (3%) - Jewish, Christian - Into Business news, reading, history, rugby, tennis and golf; - Following @BBCBreaking @Number10gov @Lord_Sugar. 44%   56%   Blue Cluster Pale Blue Cluster 31%   69%   - 20 y.o, White British, Black - Manufacturing professionals, Nurses, Teachers - From London (48%), Manchester (8%), Belfast (4%) - Muslim, Christian - Into Gaming , comedy/humor, sports; - Following @jimmycarr, @andy_murray, @rioferdy5 20%   80%   - 35 y.o., White Birtish - Senior Managers , Journalists, Writers and Lawyers - From London (50%), Manchester (3%), Leeds (2%) - Christian and Jewish - Into Politics, dining and wining, tennis, football; - Following @David_Cameron, @stephenfry, @Number10gov
  24. 24. 2! from 
 content to context!
  25. 25. © Alexandre Farto aka Vhils 2010 Most Social Media Monitoring platforms focus on just Content
  26. 26. © Alexandre Farto aka Vhils 2010 But we also wanted to understand Context and Behaviour
  27. 27. Dimensions of Social Data Content Demographics Social Graph Interest Graph Behaviours
  28. 28. Nose-to-tail indexing or Bigger Big Data Behaviours   Social  Graph   Demographics   Interest  Graph   Content  
  29. 29. Data anthropology
  30. 30. 3! from 
 analytics to intelligence
 frameworks!
  31. 31. AnalyticsIntelligence How many What time of the week Tweets/Hour? is best for what? How many What’s the brand negatives? equity?
  32. 32. Measuring Visibility
  33. 33. 4! down 
 break the social silo!
  34. 34. Predicting the Oscars Integrating social data with multiple external datasets to increase predictability
  35. 35. Images Location EXP #1 Reality Mining Call Log SMS Log Bluetooth Accelerometer Gyroscope Orientation Activity Running Apps Battery Screen Browser Searches THE  PICTURES   AS  TEMPORAL   AND  SPATIAL   MARKERS  OF   THE  JOURNEY  
  36. 36. 5! scalable 
 human-analysis!
  37. 37. 6!machinelearning!
  38. 38. 7! dataUX !
  39. 39. A data canvas
  40. 40. Visual Mining
  41. 41. Data Transparency
  42. 42. 8!decisionmaking!
  43. 43. 9! hybrid 
 methods!
  44. 44. SOCIAL PANELS > real-time segments Dynamic Segments Real-time Audience Insights Pulsar  |  Social  Data  Intelligence        @pulsar_social  |  PulsarPla]orm.com  
  45. 45. A Nation Divided? A Social Panels case study 50k readers 50k readers 23,000 Tweets 50k readers 22,000 Tweets 50k readers 50k readers 63,000 Tweets 47,000 Tweets 50k readers 32,000 Tweets 12,000 Tweets
  46. 46. A Nation Divided? How 300,000 readers of six top UK newspapers are feeling about the death of Margaret Thatcher Positive towards Thatcher Negative towards Thatcher Neutral: hidden The Daily Mail 23,000 Tweets 10% 8% 23% The Guardian 26% 16% 22,000 Tweets 19% The Daily Mirror 63,000 Tweets The Independent 47,000 Tweets The Telegraph 8% 32,000 Tweets 12% 15% 18% 23% 19%
  47. 47. 10! 
 
 making research programmable

  48. 48. Social  Data  Intelligence        @pulsar_social  |  PulsarPla]orm.com  
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