Who will win the battle for the White House to become the next President of the United States is a topic of hot debate. Much of that debate is taking place online, with plenty of people blogging, tweeting or updating social media with their thoughts on Donald Trump versus Hillary Clinton.
This provides us with a rich source of information about what people are thinking and feeling about the election race.
When our Big Data and Smart Analytics Lab analysed those comments on Twitter towards the end of July, it predicted that if the US Presidential election had been held at that time, Trump would have been the winner over Clinton. Two weeks later, a swing towards Clinton is making the result less certain.
But how accurate is this type of prediction? Well, the same lab using the same method predicted and announced in a public lecture a week before the Australian federal election that the Coalition would win over the ALP.
So it will be interesting to see what the lab’s prediction says of Trump versus Clinton as we get closer to the US election in November.
Volume of traffic
The amount of data everyone on the internet generates in just a single second is truly staggering, and it is continuing to grow, with estimates that annual global traffic will pass the zetabyte barrier by the end of 2016. That’s one trillion gigabytes (GB) of data, roughly 134GB for every man, woman and child on the planet!
Big data analytics is the discipline faced with the challenge of managing the sheer volume of data and turning it into something useful.
It makes predictions about the future based on the patterns of the past, and finds relationships buried in the data that no one has noticed. It is also very useful for running simulations to see the consequences of a particular course of action.
Its predictive power is also increasing. The analytics use smarter, faster algorithms to perform deep learning on the large volumes of data drawn from diverse sources, including from publicly accessible social media.
Surprisingly accurate predictions can now be made about trends in financial markets, fashion and tourism to name a few areas, as well as the outcome of elections.
It’s already helping businesses and governments to make strategic, well-informed decisions across a wide range of applications.
The human approach
We can improve the accuracy of simple big data prediction by using what we call the human sensor approach, developed at the Smart Analytics Lab. This recognises the whole person as an excellent data collection source.
Oceans of real-time data from social media, discussion groups, blogs and review websites are brought together along with other freely available open source data.
In the field of open data and data analytics there is a legally enforceable code that all data, regardless of where it is from, is properly anonymised. Anything that could relate to individual people is removed.
A sentiment analysis is then performed on the data that reveals what people are actually thinking about something, including how they feel about it.
This holistic approach manages to remedy many of the previous accuracy problems. For example, micro-blogs such as Twitter are very short, full of spelling errors and slang language. The new approach is able to deal with this problem.
In a project sponsored by the National Environmental Science Programthe Smart Analytics Lab is looking to use this type of data analysis to provide information on the Great Barrier Reef.
By sampling different sources of data, including social media postings and photos, it’s possible to recognise types of fish, how plentiful or scarce they are and the extent of coral bleaching. Integrating all of this data and applying deep learning allows potential environmental issues on the Reef to be identified early.
On the Gold Coast, a similar funded project is underway to gauge the satisfaction or otherwise of visitors to the Coast. Doing a sentiment analysis on the data tells us how people really feel about their holiday experience. For example, what was the accommodation like, were the beaches enjoyable and how about overall value for money?
This is information that can be used strategically by tourism operators to hone in on where they need to improve and what they already do well and could be doing more of. It can also tell the city government similar things about the public infrastructure.
Looking for a new job?
These advances in big data analytics are made possible by a convergence of three factors; cheaper yet more powerful computers, more publicly available data and smarter algorithms that learn over the time from repeated cycles of analysis.
But people skilled in data science are in high demand and are becoming increasingly rare in the employment market.
This is partly because in addition to skills in data management and machine learning the work calls for skills such as behavioural psychology, bio-infomatics, business, social anthropology and linguistics. These are skills not usually associated with the IT world.
Progressive universities are catching up with demand for data science programs that go some way to meeting the growing need. With so much talk of the jobs that won’t exist in the future, it’s good to know that there are emerging sectors where people will still be needed, for now at least.
This article was originally published on theconversation.com and can be viewed in full


Archive
- October 2024(44)
- September 2024(94)
- August 2024(100)
- July 2024(99)
- June 2024(126)
- May 2024(155)
- April 2024(123)
- March 2024(112)
- February 2024(109)
- January 2024(95)
- December 2023(56)
- November 2023(86)
- October 2023(97)
- September 2023(89)
- August 2023(101)
- July 2023(104)
- June 2023(113)
- May 2023(103)
- April 2023(93)
- March 2023(129)
- February 2023(77)
- January 2023(91)
- December 2022(90)
- November 2022(125)
- October 2022(117)
- September 2022(137)
- August 2022(119)
- July 2022(99)
- June 2022(128)
- May 2022(112)
- April 2022(108)
- March 2022(121)
- February 2022(93)
- January 2022(110)
- December 2021(92)
- November 2021(107)
- October 2021(101)
- September 2021(81)
- August 2021(74)
- July 2021(78)
- June 2021(92)
- May 2021(67)
- April 2021(79)
- March 2021(79)
- February 2021(58)
- January 2021(55)
- December 2020(56)
- November 2020(59)
- October 2020(78)
- September 2020(72)
- August 2020(64)
- July 2020(71)
- June 2020(74)
- May 2020(50)
- April 2020(71)
- March 2020(71)
- February 2020(58)
- January 2020(62)
- December 2019(57)
- November 2019(64)
- October 2019(25)
- September 2019(24)
- August 2019(14)
- July 2019(23)
- June 2019(54)
- May 2019(82)
- April 2019(76)
- March 2019(71)
- February 2019(67)
- January 2019(75)
- December 2018(44)
- November 2018(47)
- October 2018(74)
- September 2018(54)
- August 2018(61)
- July 2018(72)
- June 2018(62)
- May 2018(62)
- April 2018(73)
- March 2018(76)
- February 2018(8)
- January 2018(7)
- December 2017(6)
- November 2017(8)
- October 2017(3)
- September 2017(4)
- August 2017(4)
- July 2017(2)
- June 2017(5)
- May 2017(6)
- April 2017(11)
- March 2017(8)
- February 2017(16)
- January 2017(10)
- December 2016(12)
- November 2016(20)
- October 2016(7)
- September 2016(102)
- August 2016(168)
- July 2016(141)
- June 2016(149)
- May 2016(117)
- April 2016(59)
- March 2016(85)
- February 2016(153)
- December 2015(150)