DH Lab 1

What kinds of patterns are being examined and how are they being measured in the projects found at the Stanford Literary Lab?

This project was an attempt to quantify abstract verbal concepts in different literary concepts.

They quantified the different identifiers we use for literature: diction, genre, medium, and character. They used modern technology to analyze these identifiers for massive databases such as fanfiction.net or eighteenth and nineteenth century London novels.

 

Review the visualizations listed below.  What makes these visualizations successful? How would you measure their success?  If you had to develop a list of features that make these visualizations successful, what might those include?

 

Overall, each of these visualizations were clear and easy to read. In that way, they were successful. The more ways that a visual representation used to organize the information allowed the information to be digested more easily. For example, the use of color made the information more organized. In the Make Grey Your Best Friend project, they described the different uses of grey across digital humanities projects to note how powerful grey can be for information display.

 

However, they all hold the potential of being misleading and suppressing important information. For example, the Chicago Planning Agency (CPA) only shows options for public transportation without necessarily acknowledging the influence of privately owned vehicles. The CPA also only shows the videos and photos they have access to of particular areas within the city, which may not be representative of that part of the city. With the color example, different colors have certain connotations, as addressed in the Make Grey Your Best Friend, which again, may be misleading.

 

Go to Dirt (Digital Research Tools) and choose one (1) tool listed under “Analyze Data” and one tool listed under “Visualize Data.”  How might these tools be useful in analyzing large amounts of data?

 

Analyze Data: Altmetric

 

Altmetric combs through data on responses to academic papers on social media. I would use this tool to find interpretations of difficult articles in math, such as a recent paper published by Terence Tao. This tool could be used to search through those interpretations to find one that is understandable. Alternatively, we could use it to compare reactions to powerful articles from famous mathematicians, such as Terence Tao to similarly impactful articles from less famous mathematicians such as Robert Kantrowitz.

 

Visualize Data: Ptolemaic [a computer application for music visualization and analysis]

 

Ptolemaic visually displays audio data in different formats. This tool can be used to find trends in music throughout history. Different chord progressions and keys signatures from different genres can be represented along side each other to display the evolution of music throughout history. We could also use this tool to distinguish which chords and keys are most commonly found in pop music. Maybe we can make a correlation between key signatures and popularity of music.

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