Facebook – Big Data or Big Brother?

Facebook – it’s a website that not even Orwell could imagine existing. A digital panopticon of sorts, Facebook tracks every single move its users make in order to refine its algorithms and push more and more engaging content into the ever-willing minds of its millions of followers.

The social media giant is an example of a so-called “digital enclosure,” which can be described as “a space of universalized recognition and communication in which the places through which we move and the objects they contain recognize individuals and communicate with them (via portable devices). It is a space within which cars know their location and can rapidly access information about their surroundings, one in which supermarket shelves know when they need to be stocked and when they are being approached by someone likely to buy a particular product” (Andrejevic). The connected world Andrejevic in his paper describes  the simple business model of Facebook – shove a hyper-refined, individually personalized and constant stream of engaging content in front of a Facebook user, keep them clicking within the site as long as possible, track their actions, and then rake in the ad money from their insights and information (a.k.a “contextual advertising”).

As a social science experiment, I participated in Mat Honan’s “I Liked Everything I Saw on Facebook for Two Days. Here’s What It Did to Me.” Essentially, the experiment attempts to throw off Facebook’s content algorithms by instructing its participants to “like” every single post or ad given to them in their respective news feed for 48 hours straight and chronicle the differences before and after. A lot of information about Facebook’s internal algorithms and the data they collect can be gleaned from the company’s own Terms of Services and Privacy Policy. I used this information to help better understand why the effects of my personal version of the experiment differed greatly from Mat’s results. The first paragraph in Facebook’s Data Usage declares that they track and store everything you do.

thingsyoudo

One of the more notable consequences of this paragraph is that Facebook tracks the “types of content you view or engage with or the frequency or duration of your activities.” I am sure that message is at the bottom of the paragraph for a reason. This kind of detailed tracking allows Facebook’s algorithm to know, for instance, which videos in your news feed you watch, which videos you actually clicked on, which parts of videos you watched you actually payed attention to, the qualities of the certain portions of the video you were shown that you actually engaged with, and what videos it should feed you to keep you on Facebook longer and longer.

It also explains why as soon as I liked Purina Dog Food, ads with cute dogs prominently displayed were shown to me.

likepurina

ad

This happened almost instantly.

Overall, Honan’s experiment did not change my news feed too much at all. I constantly liked articles, pages, and photos, but nothing drastically changed. I did notice, however, that I felt I got more content relevant to my interests than usual, and it seemed more detailed than usual – instead of getting Daft Punk related news, I noticed a couple articles about the group’s specific members, and the celebrity gossip they were involved in, for instance. In true scientific fashion, I can only say that the experiment amplified what Facebook already knew about me: I like dance music, guitars, startup shenanigans, and funny pictures.

Works Cited:

Terms of service. (2015, January 30). Retrieved March 21, 2015, from Facebook, Facebook search terms    of service website,  https://www.facebook.com/legal/terms

Data Policy. (2015, January 30). Retrieved March 21, 2015, from Facebook, Facebook data policy website, https://www.facebook.com/about/privacy/

Honan, Matt. “I Liked Everything I Saw on Facebook for Two Days. Here’s What It Did to Me | WIRED.” Wired. 11 Aug. 2014. Web. 21 Mar. 2015.

Andrejevic, Mark. “Surveillance in the Digital Enclosure.” The Communication Review. Web. 21 Mar 2015.

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