I found this week’s readings were particularly mind-blowing. One thing that I would like to hone in on in this post is the 3rd point in the Boyd and Crawford reading, the idea that bigger Data are not always better data for big data. That in itself is wildly confusing but I did find that after our discussion on Thursday I am having a bit more clarity as to the implications of this statement. The text argues that “When researchers approach a data set, they need to understand — and publicly account for — not only the limits of the data set, but also the limits of which questions they can ask of a data set and what interpretations are appropriate.” (Boyd and Crawford 669-70) The example used in the text was about tweets on Twitter and our discussion was centered around health data. I think that one thing we need to consider in this whole idea is the question that Renie brought up about the definitions of a person, especially in data and online forums. While data can be useful in understanding populations as a whole, what big data tends to falter in is the human experience of individuals in the data. Therefore, in order to define a person in such a context, the researcher/anthropologist would need to be able to humanize it in some way or another. While large numbers are meaningful in their own right, the individual experience tends to be more poignant. This brings me back to thinking about the final project in this class. My group is focusing on a nurse’s account of the covid-19 outbreak. While the video that we are viewing pertains to the Pandemic and the large data sets that have resulted, what makes our media so important is that it focuses on the small size of data within the big data. This post is everywhere but I think that in order to understand a piece of media the larger context of big data is imperative in order to fully understand the gravity of the topic.