Aiden Szymanski - Blog Post 4

 I personally take much more interest in distant reading than close reading. I always found close reading to be very tedious and not overly helpful towards creating a thorough understanding of what I'm reading. I find it to be more busy work than helpful towards improving my understanding, and it always felt like more of a chore than a helpful method. Distant reading to me is a lot more helpful because. according to "The Mechanical Muse - What is Distant Reading?", it focuses a lot more on the bigger picture stuff. While I do agree with Schulz's evaluation that distant reading can oversaturate and over evaluate a text when sometimes texts are meant to be enjoyed and comprehended in a simpler manner, I think that in a general sense the exercise of evaluating text for its deeper, more complex meaning is a healthy activity for promoting literary comprehension.

I found the concept of data mining in The Digital Humanities textbook to be very interesting. While I do not necessarily find it applicable to my 9/11 Memorial Timeline that I've been studying in class, I think the mass extraction of data by a computer (especially prominent in the age of AI) is a very effective way to utilize a tool in a way to maximize efficiency and not waste your time. For example in the takeaway section on page 49, "Data mining techniques can show other patterns at a scale that is beyond the capacity of human processing (e.g., How many times does the word “prejudice” appear in 200,000 hours of newscasts?)." That kind of date extraction would be woefully inefficient if done via human labor.

Contrarily, chapter seven which discusses information visualization, is far more applicable to my project. The 9/11 timeline does a good job balancing the visualization of a documentary with audio clips, videos, and pictures, while also including the raw information you'd find in standard 9/11 literary pieces / written event documentation. The checklist for visualization was also intriguing to learn about. Looking at the first few bullets, for example:

- Assess your data: Is it composed of discrete or continuous information?

- Choose the appropriate scale: Too small a scale may make the important differences in value hard to spot, and too large may exaggerate it. If outliers stretch the scale for a few data points, consider a gap in the scale and an explanation.

- Is the labeling efficient for use? What order should the information take to be meaningful and usable (alphabetical order of country names makes them easy to find but might separate values and make them hard to compare visually)?

These are all things that would have needed to be carefully considered when making the 9/11 Memorial Timeline.