{"id":787,"date":"2016-03-30T14:48:59","date_gmt":"2016-03-30T18:48:59","guid":{"rendered":"https:\/\/eiq.knx.mybluehost.me\/website_78d26930\/bigdatacourse?p=787"},"modified":"2016-03-30T14:48:59","modified_gmt":"2016-03-30T18:48:59","slug":"not-too-impressed-with-predictive-analytics","status":"publish","type":"post","link":"https:\/\/jjsylvia.com\/bigdatacourse\/not-too-impressed-with-predictive-analytics\/","title":{"rendered":"Not Too Impressed with Predictive Analytics"},"content":{"rendered":"

\"Google-Analytics-ecomm\"<\/a><\/span><\/p>\n

 <\/p>\n

As we have discussed in many previous lectures and blogs, we all reveal tons of different kinds of data every single day as technology has become such an ingrained part of our lives. As for me, since I do much of my school work, reading, scheduling, and entertainment through my computer and phone, it seems that it would be fairly easy for a company to develop a profile on me to use for any sort of predictive analytics they might have in mind. From looking through the information I downloaded from Google, I noticed that the most revealing were my profile, Youtube, Calendar, and Hangout history, which reveal many of the broader identifiers that a company might attach to myself.<\/span><\/p>\n

Looking through my profile tells you little more than that I am a 21 year old female, but scrolling through my Youtube history is slightly more revealing; it is easy to see that I watch a lot of Christian music videos, children\u2019s music videos, French music, comedy, and history videos, as well as alternative, punk, and pop music videos. One can infer from this that I am a Christian, I have at least one child in my life, I am a francophile, and additionally one sees a glimpse into my musical preferences. These are still fairly broad categories, but already potentially useful. More specifically my emails, hangout conversations, and Calendar reveal very clearly that I am a student of French and English and that I will soon be graduating from NC State.<\/span><\/p>\n

I think any kind of company interested in targeting a young student, a young female, a francophile, a Christian, or an influencer of a child might be interested in targeting me and trying to understand how to influence me. I think any such organization could probably capture my interest in their product by aligning themselves with the interests they can see through my data. All of that said however, I haven\u2019t noticed this much through any advertising that I have seen. <\/span>The ads that I see through Google, Youtube, or Facebook seem generally to target a young female student (mostly clothing and articles for students), but don\u2019t really address any of these other potential areas that might influence me. <\/span><\/p>\n

However, from what we\u2019ve learned about predictive analytics, the process might simply more sophisticated than I am imaging, or it seems unimpressive because I am so used to the content directed towards me. Perhaps if I were to see the content directed towards my parents or someone else in a very different demographic than myself, I would understand better how I am being targeted. That is why I am interested in this idea of filter bubbles, because often times I assume that everyone else is viewing the same content as myself, but clearly this cannot be the case. Furthermore, I find these filter bubbles concerning because I would like to see more since I continue to be unimpressed by the ads and content that are directed towards me. \u00a0<\/span><\/p>\n","protected":false},"excerpt":{"rendered":"

  As we have discussed in many previous lectures and blogs, we all reveal tons of different kinds of data every single day as technology has become such an ingrained part of our lives. As for me, since I do much of my school work, reading, scheduling, and entertainment through my computer and phone, it
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