suresh.sood@uts.edu.au
or
linkedin.com/in/sureshsood
Download: slideshare.net/ssood/cool-tools-friday
July 2014
Datafication 3- First Australian Instagram Study Conducted
www.datafication.com.au
Datafication 2 : First National Study of Twitter Usage in Australia
Australians send an average of 234 million tweets per ...
Datafication
“Datafication refers to the fact that we’re looking at more
aspects of life that we never actually understood...
Roadmap to Recommender Tool
Manual Automatic Recommndation
Instagram Deception (Suspects outside of -20 & +20)
Vine Deception (Suspects outside of -5 and +5)
The Newman Model of Deception (Pennebaker et al)
Key word categories for deception mapping:
1.Self words e.g. “I” and “me”...
Kelly, Kevin (2013), A Catalog of Possibilities
http://kk.org/cooltools/
Cool Tools Categories or Topic Areas
Kelly, Kevin (2013) A Catalog of Possibilities
WORKSHOP
TOOL CHEST
RELATED STUFF
ANNO...
Tools to Support Marketing Decisions
• Approaches and methodologies to support marketing decisions:
– Segmentation tools
–...
You have to fall in love with your job.
You must dedicate you life to mastering your skill
- Jiro Ono
How to Find a Killer using Visualisation
• 1990’s Ivan Milat killed 7 backpackers making him Australia's most notorious Se...
New Sources of Information New tools:
Data Driven Applications and Internet of Things
Number of journeys made
Distances tr...
Smart Social Card System
Reader/Wifi Gateway and Active Card
Multiple Guest Bar Check In Scenario
• Multiple Guests enter Bar area in same time
• Active Tags are detected by reader in...
Smart Sandbag System
&
Smart Sleeping System
smart-dove.cn
Cool Tools
Cool Tools
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Cool Tools

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BCII Winter School Guest Lecture and Workshop

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  • Tools are defined broadly as anything that can be useful. This includes hand tools, machines, books, software, gadgets, websites, maps, and even ideas.
  • Transcript of "Cool Tools "

    1. 1. suresh.sood@uts.edu.au or linkedin.com/in/sureshsood Download: slideshare.net/ssood/cool-tools-friday July 2014
    2. 2. Datafication 3- First Australian Instagram Study Conducted www.datafication.com.au
    3. 3. 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.
    4. 4. 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
    5. 5. Roadmap to Recommender Tool Manual Automatic Recommndation
    6. 6. Instagram Deception (Suspects outside of -20 & +20) Vine Deception (Suspects outside of -5 and +5)
    7. 7. 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
    8. 8. Kelly, Kevin (2013), A Catalog of Possibilities http://kk.org/cooltools/
    9. 9. 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
    10. 10. 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).
    11. 11. You have to fall in love with your job. You must dedicate you life to mastering your skill - Jiro Ono
    12. 12. 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
    13. 13. 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
    14. 14. 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/
    15. 15. Beacon Active Card Shelf Shelf Shelf Gateway ServerMonitor InternetInternet Supermarket control room
    16. 16. Smart Social Card System Reader/Wifi Gateway and Active Card
    17. 17. 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”
    18. 18. Smart Sandbag System & Smart Sleeping System smart-dove.cn
    19. 19. Internet of Things “trillion sensors” Source: www.tsensorssummit.org
    20. 20. 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

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