Information Visualization & Distant Reading

In chapter 6, we gained a wider perspective of how information visualization helps us interpret data easier. According to the textbook, they are “metrics expressed as graphics” (Drucker  86) that “are used to make this quantitative data legible” (Drucker 86). Not everyone has the capability to easily read data spreadsheets, therefore this practice can help condense all of the data. Any mathematical number can be turned into visualizations such as graphs, charts, or diagrams. The textbook includes various examples of these, typically two at a time to compare. One example is on page 89, where a line graph and pie chart are presenting the same data. Drucker put the line graph and pie chart together because he knows those two are not similar visualizations at all. This example was helpful for me to physically see how different kinds of visualizations can organize the same numerical data. Below, I inserted a photo of the various kinds of visualizations to show that they are not limited to data tables and graphs. 

Distant reading is an important skill to have when looking at digital humanities. Unlike close reading, which is “our preferred contemporary term for a heterogeneous and largely unorganized set of practices and assumptions” (Jin 106), distant reading does not create knowledge on an individual scale but instead an expanded one. According to the reading Problems of Scale, Jay Jin argues that “various rhetorics of scale involved in ‘distant reading’ can be understood metonymically, structured by the logic of part-part relationships” (Jin 105). 

In What is Distant Reading, Franco Moretti believes that distant reading is “understanding literature not by studying particular texts, but by aggregating and analyzing massive amounts of data” (Schulz). The Italian literary scholar claims that in order for humans to understand literature, we have to stop reading physical books. 

The project we looked at in class, "Six Degrees of Francis Bacon,” organizes thousands of relationships between early modern figures into a digital reconstruction where students can interact with the connections easier. With the various data, I like how I am able to click on a certain scholar and it breaks down into those specific ties. 

In “Yesterday, Today, and Tomorrow” the emotions felt during the 2020 pandemic are organized into colorful dots as data. I thought it was cool how I was able to click on a certain month and see how most people felt during that time period.