BCII Winter School Guest Lecture and Workshop

1. suresh.sood@uts.edu.au
or
linkedin.com/in/sureshsood
Download: slideshare.net/ssood/cool-tools-friday
July 2014

3. Datafication 3- First Australian Instagram Study Conducted
www.datafication.com.au

4. Datafication 2 : First National Study of Twitter Usage in Australia
Australians send an average of 234 million tweets per month and 5,000 tweets per minute, a new Twitter
study by advertising agency The Works has found. Aussie females are more likely to retweet than males
and most retweets occur on Mondays, according to the agency's 'datafication' research project. Douglas
Nicol, creative partner and director at The Works, said the study was designed to help marketers talk to
consumers more effectively. “There’s a lot of hype around social media. Using research from datafication,
we are able to equip Australian marketers with no nonsense practical advice,” Nicol said.“This in turn will
help marketers appeal directly to an audience. We believe that in turn, this will boost the way people view
and talk about a brand or product online.”
Lovers, carers and jesters were identified as the top three archetypical personalities on Twitter.
According to the study marketers can talk most effectively to lovers by being passionate, carers by being
gentle and jesters by being mischievous.“If you understand what drives the motivations behind
Australians you will be in a better position to connect with them,” Nicol said. Almost 11% of the Australian
population is on Twitter and of those users 46% are male and 54% are females.
The study also found that Sydney hosted the largest population of Twitter users while Hobart is
responsible for the most tweets per capita.
'Datafication', which was supported by the University of Technology Sydney (UTS), analysed the most
popular words used in Twitter over an eight week period to rank motivations and behaviours on the
social site.
Software created by Dr Suresh Sood, a social media expert at UTS, then analysed the data to produce
the insights into what individuals are doing on Twitter.
'Datafication' is set to launch as a real-time service for the agency’s clients early next year.

5. Datafication
“Datafication refers to the fact that we’re looking at more
aspects of life that we never actually understood as being
informational before…So what we’re seeing with social media
companies is they’re actually datafying aspects of the life that
we never really saw that could be datafied. So for example
Facebook datafies our friendships. Twitter datafies our whispers
or maybe our stray thoughts. And LinkedIn datafies our
professional contacts…what big data means is we are able to
learn things about ourselves at the population level, at a huge
scale, that we never could in the past. So lots of different
disciplines, in one case sociology, totally gets upended. Because
in the past you ran small studies on small groups, now you’re
looking at it in population scale size.
“Datafication refers to the fact that we’re looking at more
aspects of life that we never actually understood as being
informational before…So what we’re seeing with social media
companies is they’re actually datafying aspects of the life that
we never really saw that could be datafied. So for example
Facebook datafies our friendships. Twitter datafies our whispers
or maybe our stray thoughts. And LinkedIn datafies our
professional contacts…what big data means is we are able to
learn things about ourselves at the population level, at a huge
scale, that we never could in the past. So lots of different
disciplines, in one case sociology, totally gets upended. Because
in the past you ran small studies on small groups, now you’re
looking at it in population scale size.
Kenneth Cukier, 2014, “Birth of Datafication”, http://bigthink.com/videos/the-birth-of-datafication

6. Roadmap to Recommender Tool
Manual Automatic Recommndation

7. Instagram Deception (Suspects outside of -20 & +20)
Vine Deception (Suspects outside of -5 and +5)

8. The Newman Model of Deception (Pennebaker et al)
Key word categories for deception mapping:
1.Self words e.g. “I” and “me” – decrease when someone distances
themselves from content
1.Exclusive words e.g. “but” and “or” decrease with fabricated content
owing to complexity of maintaining deception
1. Negative emotion words e.g. “hate” increase in word usage owing
to shame or guilty feeling
1.Motion verbs e.g. “go” or “move” increase as exclusive words go
down to keep the story on track

9. Kelly, Kevin (2013), A Catalog of Possibilities
http://kk.org/cooltools/

10. Cool Tools Categories or Topic Areas
Kelly, Kevin (2013) A Catalog of Possibilities
WORKSHOP
TOOL CHEST
RELATED STUFF
ANNOUNCEMENTS
DEAD TOOLS
READERS' GIFTS
BACKPACKING
AUTONOMOUS MOTION
LIVING ON THE ROAD
VEHICLES
TIPS
MATERIALS
MEDIA TOOLS
DWELLING
FAMILY
SCIENCE METHOD
INNER SPACE
WORKPLACE
LIVELIHOOD
PLAY
SOMATICS
CLOTHING
GENERAL PURPOSE TOOLS
SOURCE WANTED
EDIBLES
GARDENS
LIFE ON EARTH
BIG SYSTEMS
CONSUMPTIVITY
COMPUTERS
PAPER WORLD
PHOTOGRAPHY
COMMUNICATIONS
AURAL
VISUAL MEDIA
KITCHEN
CULTURE
DESTINATIONS
COMMUNITY
CRAFT
HEALTH
LEARNING
HOMESTEAD
DESIGN
UNCATEGORIZED

11. Tools to Support Marketing Decisions
• Approaches and methodologies to support marketing decisions:
– Segmentation tools
– Perceptual mapping
– Survey and Panel based choice models
– Pre-test market models
– New product models
– Aggregate marketing response models
– Sales force allocation models
– Customer satisfaction models
– Game theory models
– Customer lifetime models
– Marketing metrics
Roberts, John H., Ujwal Kayande, and Stefan Stremersch. "From academic research to marketing practice:
Exploring the marketing science value chain." International Journal of Research in Marketing (2013).

13. You have to fall in love with your job.
You must dedicate you life to mastering your skill
- Jiro Ono

14. How to Find a Killer using Visualisation
• 1990’s Ivan Milat killed 7 backpackers making him Australia's most notorious Serial Killer
• Everyone in Australia was a suspect
• Enormous volumes of data from multiple sources
 RTA Vehicle records
 Gym Memberships
 Gun Licensing records
 Internal Police records
•
• Police applied visualisation techniques (NetMap) to the data
• Reduced the suspect list from 18 million to 230
• Further analysis with the use of additional information reduced this to 32

15. Square
Kilometer Array
(SKA)
• The data collected by SKA in a single day take nearly two million years to playback on an MP3 player
The SKA central computer has processing power of about one hundred million PCs.
• The SKA will use enough optical fiber linking up all the radio telescopes to wrap twice around the Earth.
• The dishes of the SKA when fully operational will produce 10 times the global internet traffic as of 2013.
• The aperture arrays in the SKA could produce more than 100 times the global internet traffic as of 2013.
• The SKA will generate enough raw data to fill 15 million 64 GB MP3 players every day.
• The SKA supercomputer will perform 1018 operations per second - equivalent to the number of stars in
three million Milky Way galaxies - in order to process all the data that the SKA will produce.
• The SKA will be so sensitive that it will be able to detect an airport radar on a planet 50 light years away.
• The SKA will contain thousands of antennas with a combined collecting area of about one square
kilometer (that's 1,000,000 square meters).
• Previous mapping of Centaurus A galaxy took a team 12,000 hours of observations and several years.
SKA ETA 5 minutes !
To the scientists involved, however, the SKA is no testbed, it’s a transformative instrument
which, according to Luijten, will lead to “fundamental discoveries of how life and planets and
matter all came into existence. As a scientist, this is a once in a lifetime opportunity.”
Sources: http://bit.ly/amazin-facts & http://bit.ly/astro-ska
Galileo

16. New Sources of Information New tools:
Data Driven Applications and Internet of Things
Number of journeys made
Distances travelled
Types of roads used
Speed
Time of travel
Levels of acceleration and braking
Any accidents which may occur
http://tacocopter.com/

17. Beacon
Active Card
Shelf Shelf Shelf
Gateway
ServerMonitor
InternetInternet
Supermarket control room

19. Smart Social Card System
Reader/Wifi Gateway and Active Card

20. Multiple Guest Bar Check In Scenario
• Multiple Guests enter Bar area in same time
• Active Tags are detected by reader in Bar
• Tag IDs are sent to server
• Guests names and drink preference are retrieved and
pushed to waiter mobile or wearable device
• Guest names are listed on mobile device UI, which can
be sorted by drink preference and distance between
guest and bar
• Waiter prepares guests preferred drink and serves
guests updating system as “served”

21. Smart Sandbag System
&
Smart Sleeping System
smart-dove.cn

22. Internet of Things
“trillion sensors”
Source: www.tsensorssummit.org

23. Cool Tools Session
•Tools are increasingly mobile apps and cloud services
e.g. lie detector transforms to online lie detection
•Form groups of 5 to 7
•60 min group review of 2 tools via URL (black & blue)
•~ 3 min elevator pitch – see form and prompts
•Return forms for collation and sharing