Privacy. It’s a subject matter that we all think we’re entitled to. It’s something we all value. It’s something that as a general online populous we have a cavalier assumption that we possess, and realistically, online privacy is something the average social media user knows very little about. Privacy. It’s a state where one is neither disturbed nor observed by other people; it is the state of being free from unwanted public attention. But does privacy really exist in the digital world? My profile is ‘private’, so I’m protected…right?
The emergence of Web 2.0 has enabled the rise of a digital culture. A locus where individuals experience and display connection, via networked publics, in both the physical and online domains. Regardless of whether these two domains mirror each other, as Hinton and Hjorth (2013) state “the mere fact that you are connected to the Internet, immediately compromises your privacy”.
When discussing Social Network Sites (SNSs), there are two principal concerns regarding a user’s privacy. The first is the well documented and examined issue of user-to-user privacy. The second concern is the more recent query of a user’s privacy in regards to the SNS itself.
OMG! Are They Stalking Me?
Hinton and Hjorth (2013) argue that in terms of safeguarding one’s privacy from other users, one must look beyond the oversimplified notion of privacy settings. Whether it is through a private Facebook or Instagram profile, ‘protecting’ your tweets or customising who can view your story on Snapchat, each individual SNS provides the user with some ability to protect their privacy (however it is important to note that these privacy settings are not the default setting on most platforms). Hinton and Hjorth (2013) propose that the most effective manner to safeguard one’s privacy is not through SNSs’ privacy settings but instead through careful selection of content and whom to share it with. However, this generates a dilemma of contradiction between online intimacy and privacy, particularly with the younger generation. An increasing number of youths, driven by a heightened need for intimacy, are willingly decreasing their online privacy in the hopes of greater connection (Boyd & Marwick, 2011). Individuals are utilising new methods to control their online presence, deliberating the benefits of gained social capital against the cost of privacy (Hinton and Hjorth, 2013) instead of simply relying on the privacy safety nets of SNSs.
An equally comical and terrifying example of the importance of utilising established privacy settings comes from the website www.iknowwhereyourcatlives.com. The website uses reverse geocoding to scan photos of cats that have been publically posted to various SNSs. The software uses locational geodata to overlay the photos onto Google Maps, in essence showing where the image was taken. They have placed thousands of cats to locations all around the world, all of which are accurate to 7.8 metres. The website was created to demonstrate the ease of access to information and reinforce the extent of information that users display when posting on SNSs.
Figure 1: Screenshot of Iknowwhereyourcatlives.com http://iknowwhereyourcatlives.com/cat/b922642bfa
Whilst it’s disconcerting to think what other users might be able to gather regarding our online habits, it is more worrisome to imagine the breadth of information SNSs possess about ourselves and what they do with that data.
Unfollow Me Facebook
SNSs themselves elicit severe privacy criticism, due to their exposure to and management of large amounts of personal data. Hinton & Hjorth’s (2013) approach to privacy from SNSs’ surveillance questions whether the user is the controller or if they are being controlled. The authors propose that SNSs are the junction between networked publics and commercial interests, which results in a murky combination. “Where there are people, there are markets, and the internet…[has] the potential to offer up something that mass media could not: a source of highly detailed information about audiences.” (Hinton & Hjorth, 2013). A user’s personal information and habits are incredibly valuable to third parties, as can be seen with the rise of targeted advertising. However, this value is considerably heightened when the information of many connected people in a group is aggregated (Chen & Michael, 2012). Two main methods are utilised to gather this personal information; the use of privacy policies to authorise a user’s privacy disclosure and data mining (Chen & Michael, 2012).
“We collect the content and other information you provide when you use our Services, including when you sign up for an account, create or share, and message or communicate with others. This can include information in or about the content you provide, such as the location of a photo or the date a file was created.”
In other words they have access to all metadata of the user, and in addition to personal information, this also includes one’s IP address and access to tracking cookies (Chen & Michael, 2012).
Most other SNSs’ privacy policies read similarly, they have the right to collect and analyse every post, comment and hashtag users produce. More so, you agree that they are able to share that information with third parties. This is an alleged breach of privacy laws that continues to be investigated by US courts (Brandom, 2016; McGrath, 2014). The link to popular SNS’s privacy policies are linked below.
Besides the annoyance of every piece of advertising mirroring your last online purchase, what is the harm in an SNS collating this information? The introduction of data mining has changed the consumer information and privacy landscape. Data mining is the process where fragments of user information is extracted, collated and integrated from several locations. These include but aren’t limited to, one’s personal profiles, email, tracking cookies and even friends of friend’s profiles (Cleve & Lammel, 2016), and the implications of this technology stem far beyond targeted advertising.
Figure 2: A visual depiction of the social media data mining process
For example, a user may post regularly about eating unhealthy foods, check into a fast food restaurant and comment on a friend’s status about how unmotivated they are to exercise, with weeks or months in between related activities. Data mining of this information, then sold to an insurance company, has the potential to lead to an increase in one’s health insurance premiums. Similarly, US based data mining company Rapleaf Inc. faced scrutiny about data mining social media for users’ spending habits to estimate users’ credit scores (Betancourt, 2010). Knowledge is power, and with a world of information available on SNSs, data mining is big business.
How Orwellian can we get?
Deep packet inspection (DPI) is data mining on steroids and it’s the final straw for privacy. DPI is a form of data processing whereby the technology analyses data sent by one’s computer and re-routes it accordingly (Fuchs, 2013). The technology was initially developed as a means of virus protection and has since evolved into the process of mass surveillance. DPI is the technology China utilises for its Internet censorship and similarly it was the process with which Edward Snowden was concerned (Geere, 2012). Although the technology is currently predominantly used by Internet service providers, government and corporations like NASA, there are potential commercial implications for SNSs. These include all encompassing user surveillance and the ability to re-route users to preferential websites (Fuchs, 2013). Additionally, with Facebook this week launching their plans for augmented reality through their new Camera Effects Platform, with the combination of improving surveillance technology, not only will they be analysing what we post, they’ll be following what we see and do.
We’re often told to think before we post, but perhaps we should be thinking whether to post at all. Because if you know where my cat lives, what else could you possibly know about me? And how much is that information worth to the highest bidder?
Betancourt, L (2010, March 20) How companies are using your social media data, Mashable Australia. Retrieved from http://mashable.com/2010/03/02/data-mining-social-media/#YJnc1ey_TEqx
Boyd, D. & Marwick E., Social Privacy in Networked Publics: Teens’ Attitudes, Practices, and Strategies (September 22, 2011). A Decade in Internet Time: Symposium on the Dynamics of the Internet and Society, September 2011. Available at SSRN: https://ssrn.com/abstract=1925128
Brandom, R (2016, May 19) Lawsuit claims Facebook illegally scanned private messages, The Verge. Retrieved from http://www.theverge.com/2016/5/19/11712804/facebook-private-message-scanning-privacy-lawsuit
Cleve, J., & Lämmel, U. (2016). Data mining. Berlin ;Boston: De Gruyter Oldenbourg
Chen, X & Michael, K. (2012) Privacy Issues and Solutions in Social Network Sites, IEEE Technology and Society Magazine, Vol. 31, No. 4, pp. 43-53.
Fuchs, C. (2013) Societal and ideological impacts of deep packet inspection internet surveillance, Journal of Information, Communication & Society, Vol. 16, No. 8, pp. 1328-1359.
Geere, D (2012) How deep packet inspection works, Wired. Retrieved from http://www.wired.co.uk/article/how-deep-packet-inspection-works
Hinton, S & Hjorth, L (2013) Undestanding Social Media (1st edn), Thousand Oaks, Californs: Sage Publications.
McGrath, P (2014, January 3) Facebook alleged to have sold information in users’ private messages, ABC news. Retrieved from http://www.abc.net.au/news/2014-01-03/facebook-sued-for-selling-information-in-users-private-messages/5183904
Privacy in Oxford English Dictionaries Online. Retrieved 25th April 2017 from http://www.easybib.com/reference/guide/apa/dictionary