Big Data: clever or creepy?
Week 9 of Internet, Self, and Beyond focussed on big data and telemetrics. As has been discussed over the semester, new media has provided a multitude of opportunities to share, communicate, and connect with others.
According to Siegel (2013, 3 – 5), “data embodies a priceless collection of experience of which to learn”, and that each digital experience “can be encoded as data and warehoused”. New media technology has a newfound capacity for intelligence, and it is giving us the ability to understand ‘big data’, visualise and make predictive notions based on analysis of this data. From this, we can learn more about how consumers and society operate.
The Dark Side of Data - posted by The Economist
It is large corporations and companies that have access to this data, mainly because they have both the financial and technological resources to store this information. I must say that the idea of ‘big data’ concerns me quite greatly. It seems unethical for large corporate entities to have access to private user information, which subsequently gives them the ability to manipulate this data for their own financial gain. As the video The Dark Side of Data posted by The Economist explained, over 1,800,000,000 people have access to your information on Facebook – and that’s under default privacy settings (2012). In addition to this, approximately 72% of privacy policies allow third parties to track our Internet activity and online behaviours (The Economist, 2012).
Siegel noted, big data “uncovers what drives people and the actions they take – what makes us tick and how the world works…with the new knowledge gained, prediction is possible” (2013, 4). An example of utilising personal data for predictive analytics is online pop up and sidebar advertisements. These ads are selected by online advertisers to reflect previous sites you have personally visited, making you more inclined to click on their ad. Large corporations such as Google, Facebook or Twitter collect a significant amount of users’ personal data, and then sell this to online advertisers.
An email I received from Coles recently about my 'top in-store specials' - data that was received and analysed via my Flybuys account (which is creepy...)
As Darryl Woodford (2014) mentioned in the lecture, big data is frequently used as business intelligence to help with target advertising towards individual consumers – it is “a currency across industry”. This is achieved through analysing the data regarding the items or products a customer has purchased previously, commonly referred to as a ‘purchase history’. I have personally experienced this, through Coles Supermarkets. I am often sent emails by the chain informing me which of my ‘favourite’ products were on sale or suggesting special deals I would be interested in. When it first happened, I found it extremely creepy, namely because I don’t have an online account with Coles (for online shopping) and I had never done a survey or something to give them this information. After a while I realised that Coles had retrieved and then analysed this data from my Flybuys account, which records purchases whenever I scan my Flybuys card. Whilst Coles probably intends systems like this to be efficient and helpful for consumers, it is quite worrying knowing they have all this data about my consumer behaviour that I didn’t give them.
REFERENCES:
The Economist. 2012. “The Dark Side of Data” YouTube video, posted June 26. Accessed May 11, 2014. https://www.youtube.com/watch?v=ahZGEusG13A
Siegel, Eric. 2013. “Introduction: The Prediction Effect”. In Predictive Analytics: The power to predict who will click, buy, lie or die, edited by Eric Siegel, 1 – 16. Hoboken: Wiley. Accessed May 11, 2014. https://qutvirtual3.qut.edu.au/qv/olt_material_search_p?p_unit_code=KCB206
Woodford, Darryl. 2014. “Week 9 – New Media, Big Data and Telemetrics”. Accessed May 11, 2014. http://www.dpwoodford.net/wp-content/uploads/2014/02/KCB206-Big-Data-Lecture_Small.pdf








