{"id":761,"date":"2016-03-30T12:20:13","date_gmt":"2016-03-30T16:20:13","guid":{"rendered":"https:\/\/eiq.knx.mybluehost.me\/website_78d26930\/bigdatacourse?p=761"},"modified":"2016-03-30T12:20:13","modified_gmt":"2016-03-30T16:20:13","slug":"the-advertise-that-bind-my-data-and-predictive-analytics","status":"publish","type":"post","link":"https:\/\/jjsylvia.com\/bigdatacourse\/the-advertise-that-bind-my-data-and-predictive-analytics\/","title":{"rendered":"The Advertise That Bind: My Data and Predictive Analytics"},"content":{"rendered":"<p>Although I&#8217;m admittedly cautious about what information I share online, I still don&#8217;t have much of a doubt that I provide a wealth of data that could be of use to certain third party interests. Much of what anybody would need to know&#8211;or like to know&#8211;about my interests could be mined from my search history. Everything from the sites I visit, to the places I do my shopping provides useful insight into not only how I might be reached, but how I might be persuaded. In other words, what I&#8217;m searching for and what I&#8217;m reading about leads to targeting on an entirely more complex level than I would have previously considered. <\/p>\n<p>In the words of Viktor Mayer-Schonberger, &#8220;In the media, the content that gets created and publicized on websites like Huffington Post, Gawker, and Forbes is regularly determined by data, not just the judgment of human editors. The data can reveal what people want to read about better than the instincts of seasoned journalists.&#8221; As a consequence, the modern media landscape not only dictates how the content is tailored, but the content itself. As I have a heavy interest in politics, I would say that I specifically stand to be targeted by political interests. This is only exacerbated by the fact that we&#8217;re in a watershed election year, but I&#8217;ll delve further into that later. <\/p>\n<p>I guess you could say that for awhile I was stuck in my own filter bubble. I was reading a little too much Orwell and Huxley&#8211;and as a result&#8211;I&#8217;d crafted at least a few conspiracy theories on how corporations could exploit my data. However, in the time since, I&#8217;ve pretty much come to accept that this is just the nature of things, and that everything comes with the territory. I realize that the predominant number of ads, messages, and videos are merely the product of choices that I&#8217;ve consciously made with my own data contribution. I&#8217;ve agreed to the terms and conditions, and I&#8217;ve sat through more than a few classes that were considerably critical of media, so I essentially know what I&#8217;m getting myself into. If anything, while I&#8217;m more wary of predictive analytics, not a lot has changed as a result. <\/p>\n<p>The data that Google has compiled from my online activity is particularly interesting. Among the most active folders in terms of data accrual, are Bookmarks, Drive, and Youtube. The compilation itself really speaks to the key insights of the readings and this post. My Bookmarks reveal where I&#8217;m going, and where I intend to return. My Drive reveals what I&#8217;m sharing. And my Youtube account&#8211;which is probably the most active of the three&#8211;shows what I&#8217;m watching and what I&#8217;m likely to watch. Third party interests, namely those political in nature, can and likely will use this information to endorse their candidates, platforms, and agendas in effort to win me over and persuade me to invest in what they&#8217;re selling. At the end of the day, that&#8217;s what this is all about anyway.   <\/p>\n","protected":false},"excerpt":{"rendered":"<p>Although I&#8217;m admittedly cautious about what information I share online, I still don&#8217;t have much of a doubt that I provide a wealth of data that could be of use to certain third party interests. Much of what anybody would need to know&#8211;or like to know&#8211;about my interests could be mined from my search history.<br \/><a class=\"moretag\" href=\"https:\/\/jjsylvia.com\/bigdatacourse\/the-advertise-that-bind-my-data-and-predictive-analytics\/\">+ Read More<\/a><\/p>\n","protected":false},"author":16,"featured_media":764,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[1],"tags":[],"class_list":["post-761","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-uncategorized"],"_links":{"self":[{"href":"https:\/\/jjsylvia.com\/bigdatacourse\/wp-json\/wp\/v2\/posts\/761","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/jjsylvia.com\/bigdatacourse\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/jjsylvia.com\/bigdatacourse\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/jjsylvia.com\/bigdatacourse\/wp-json\/wp\/v2\/users\/16"}],"replies":[{"embeddable":true,"href":"https:\/\/jjsylvia.com\/bigdatacourse\/wp-json\/wp\/v2\/comments?post=761"}],"version-history":[{"count":3,"href":"https:\/\/jjsylvia.com\/bigdatacourse\/wp-json\/wp\/v2\/posts\/761\/revisions"}],"predecessor-version":[{"id":765,"href":"https:\/\/jjsylvia.com\/bigdatacourse\/wp-json\/wp\/v2\/posts\/761\/revisions\/765"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/jjsylvia.com\/bigdatacourse\/wp-json\/wp\/v2\/media\/764"}],"wp:attachment":[{"href":"https:\/\/jjsylvia.com\/bigdatacourse\/wp-json\/wp\/v2\/media?parent=761"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/jjsylvia.com\/bigdatacourse\/wp-json\/wp\/v2\/categories?post=761"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/jjsylvia.com\/bigdatacourse\/wp-json\/wp\/v2\/tags?post=761"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}