For this week’s post, I want to keep the conversation we started in class today when I briefly mentioned patterns and when Lauren asked “what or who counts as a person?” The big data isn’t only about the big data but what social media companies can assume when analyzing that big data. When we go online and surf the web, we create that data that companies can pick out certain patterns.  For example, my phone knows that I usually eat pizza once every month which happens in the first week of every month. That means that pizza restaurants can use that data and pattern to make sure I get a Dominos advertisement on every social media at the right time.

The problem that I struggle with is brought up in Boyd and Crawford’s: “Too often, Big Data enables the practice of apophenia: seeing patterns where none actually exist, simply because enormous quantities of data can offer connections that radiate in all directions.”(668) This made me think that the large number of data can lead to wrong assumptions of the users which pushes me to think that data can never represent accurately its users. That data has to be interpreted which means it can also be misinterpreted and it has limitations. The reality of it is that the data doesn’t care if you are a person or not and it will never completely represent someone.