Data and Visualization and Mining

Chapters 6 and 7 taught me a lot of new things in terms of data mining and visualization. To begin, data visualization is putting a given set of data into a graph. They help to see patterns that are happening through different types of graphs such as; bar, line, bubble, and pie charts. The important part about data visualization is how you choose to express it, as said in the text "The challenge is to understand how the information visualization creates an argument and then make use of the graphical format whose features serve your purpose" (90). The key thing to note when it comes to rhetorical graphs is questioning the creator of the content as sometimes it can be deceptive. I also learned about networks and the complexion and how it "is that the development of the system cannot be predicted-- because the processes are nonlinear and/or non-deterministic from a statistical standpoint. 


Data Mining as defined in the book "is an automated analysis that looks for patterns and extracts meaningful information in digital files"(110).  And distance reading is the analysis of information about a text without being in the actual text.  Distance reading helps to capture a broadened understanding of what a person is reading. However, distance reading is based of an interpretation as it is a broad look at the text rather than an up close and personal one like close reading. 

Comments

  1. Distance reading seems like such a weird concept until you realize that you do it on so many occasions-especially in school

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  2. I like how you phrased it: 'They help you see patterns that are happening through different types of graphs such as bar, line, graph, bubbles, and pie charts.' Patterns is a good way of describing the work of data mapping.

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  3. It is definitely like a zooming out on a text and looking for patterns.

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