Twenty minutes after waking up this past Monday morning, I was already contributing to big data. I had a vegan friend who was visiting me in Raleigh, so I googled “vegan-friendly restaurants in Raleigh, NC.” I then watched the two final episodes of Making a Murderer on Netflix. As the final episode ended, I noticed that Netflix offered a suggestion for my next\u00a0show, with the statement “Since you watched Making a Murderer”…Curious as to what the suggestions were, I looked at the options and realized that they all seemed very interesting. After realizing that Valentine’s Day was approaching, I decided to google “easy way to make chocolate covered strawberries.” I also needed a dinner idea so I clicked on an article that was titled, “Easy Dinners for College Students.”\u00a0Later in the day, I browsed\u00a0Facebook for a bit and noticed a few articles on the side bar that were advertising for planning my next cruise. My friends and I had booked our cruise tickets on my laptop and Facebook remembered this fact, tapering it’s ads to fit my possible interests. Since I had previously “liked” a vast array of politically affiliated sites, those pages were popping up on my timeline. The “people you may know” side bar also popped up, indicating that Facebook tracked my recent friends and our mutual friends.<\/p>\n
I also noticed that after logging into Amazon Prime to look for Valentines present for my boyfriend, my credit card information had been retained on the site. This was slightly convenient, as I didn’t have to retype in the numbers, however, it was also alarming because of how easily somebody could hack into my Amazon account and gain access to my credit cards. After finding what I needed for my boyfriend’s Valentine’s Day present, Amazon had a “You may also like” statement at the bottom of the page, with pictures of more awesome gift ideas. I proceeded to spend 15 more minutes browsing all the clever ideas and getting angry that I had already bought something before looking through these.<\/p>\n
Later in the day, I decided to watch a few lectures for my online class. This required a Mediasite login which uses my unity ID information. I also logged into Gmail and checked a few emails from professors. Around 4 PM, I began to browse reddit. This site had saved my favorite subreddits that were at the top of the site. This allowed me to easily access the pages that I most frequently visited (WorldNews, AskScience, Psychology, etc). Big data is able to gather a significant amount of information from my use of technology. A few items of information that they could have gathered would be: the fact that I am a college student, the fact that I am in a relationship, the fact that my boyfriend likes Game of Thrones (considering my Valentine’s Day purchase), the fact that I am embarking on a cruise for spring break, my affinity towards murder documentaries, the fact that either myself or my friend is vegan, my interest in reading science and psychology articles, my participation in an online class, my use of gmail, and probably my political affiliation. This experience was very enlightening because I never realized how much information I put out there. It was also alarming because some of the information that is gathered is not indicative of my actual personality or interests. For example, the search made for vegan restaurants was for a friend who was visiting and not for myself. This has caused me to question some things: Will future employers consider my online presence to be of greater significance than my literal presence? Will information exchanged via email, like rejections or acceptances from grad schools\/jobs be taken into consideration when somebody is hiring me?<\/p>\n","protected":false},"excerpt":{"rendered":"
Twenty minutes after waking up this past Monday morning, I was already contributing to big data. I had a vegan friend who was visiting me in Raleigh, so I googled “vegan-friendly restaurants in Raleigh, NC.” I then watched the two final episodes of Making a Murderer on Netflix. As the final episode ended, I noticed
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