suresh.sood@uts.edu.auor

linkedin.com/in/sureshsood

Download: slideshare.net/ssood/cool-tools-friday

July 2014

Datafication 3- First Australian Instagram Study Conductedwww.datafication.com.au

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.

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

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” – 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

Kelly, Kevin (2013), A Catalog of Possibilitieshttp://kk.org/cooltools/

Cool Tools Categories or Topic AreasKelly, Kevin (2013) A Catalog of Possibilities

WORKSHOPTOOL CHESTRELATED STUFFANNOUNCEMENTSDEAD TOOLSREADERS' GIFTSBACKPACKINGAUTONOMOUS MOTIONLIVING ON THE ROADVEHICLESTIPSMATERIALSMEDIA TOOLSDWELLINGFAMILY

SCIENCE METHODINNER SPACEWORKPLACELIVELIHOODPLAYSOMATICSCLOTHINGGENERAL PURPOSE TOOLSSOURCE WANTEDEDIBLESGARDENSLIFE ON EARTHBIG SYSTEMSCONSUMPTIVITY

COMPUTERSPAPER WORLDPHOTOGRAPHYCOMMUNICATIONSAURALVISUAL MEDIAKITCHENCULTUREDESTINATIONSCOMMUNITYCRAFTHEALTHLEARNINGHOMESTEADDESIGNUNCATEGORIZED

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).

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 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

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

New Sources of Information New tools: Data Driven Applications and Internet of Things

Number of journeys madeDistances travelledTypes of roads usedSpeedTime of travelLevels of acceleration and brakingAny accidents which may occur

http://tacocopter.com/

Beacon

Active Card

Shelf Shelf Shelf

Gateway

ServerMonitor

InternetInternet

Supermarket control room

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 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”

Smart Sandbag System&

Smart Sleeping System

smart-dove.cn

Internet of Things“trillion sensors”

Source: www.tsensorssummit.org

Cool Tools Session

•Tools are increasingly mobile apps and cloud servicese.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