Hi Chris,
After completing Task 9, I reviewed our course’s Student Webspaces. From reading your post, I learned about the ability to manually change the data. I didn’t know this was possible by simply dragging the nodes. I see how this helped you make better sense of the data, as evidenced in your before and after images. I found from a visual standpoint that viewing the size of nodes was a quick reference.
Like you, I wasn’t sure why we were grouped together in modularity _class group #1. I saw more commonalities for song choices with other participants. Did you find connections that I missed?
I agree that there “isn’t enough information available to draw any strong conclusions about the revisioning of each of our song choices and the commonalities between them”. From the data provided, we can only make assumptions, which as we understand from data, is not reliable and may result in misinterpretations. Further analysis would be needed as well as additional information in order to form reliable conclusions from the data.
I appreciate your section on implications and the information you researched on algorithmic oppression. I found an interesting site called GapMinder. Physician and scholar Hans Rosling was the co-founder and chair of GapMinder Foundation, a non-profit organization that promotes education in “fighting global misconceptions” in information. Rosling has worked in the field of data and the promotion and use of data to explore developmental issues. The link to GapMinder (in references) provides a fascinating look at stats and how too often data and stats are not reliable. “Facts don’t appear automatically in our heads like opinions do. Facts have to be learned” (gapminder.org). You may find the site interesting as it supports critical thinking and reducing biases in a number of global areas of concern.
References:
GapMinder.org. (n.d.). Retrieved from https://www.gapminder.org/factfulness/
