Lab #1 Cultural Analytics

Zach Kleinbaum, Cooper Halpern

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

The projects at the Stanford Literary Lab are designed to analyze literary trends. These projects track the patterns and relationships between textual and thematic elements of texts in order to tell more about a genre or the time period when the piece was written. These projects all attempt to place the scope texts within a defined, larger picture by elucidating the patterns which connect the texts to the research question. For example one project tracks the relationship between the race of fictional characters and how they are perceived in the literature. The patterns are measured by tracking the descriptive terms associated with particular characters and then connecting those adjectives to the character’s stated ethnicity. This project allows for an observation of the way race is viewed at a specific point in time based on when the book was written. A second project looks at how the gender of the author influences the way genders are depicted in literature based on the dialogue of the characters in the book. This too is tracked by analyzing the text and observing the words used by certain genders. This project can help us gain a deeper insight into the role of gender in the development of the novel.

  1. Review the visualizations listed below.  What makes these visualizations successful?  http://www.visualisingdata.com/2015/01/new-visual-package-chicago-planning-agency/

This visualization depicts the past, present, and future plans of Chicago’s transit, roads, and freight. It successfully takes a multimedia approach by smoothly blending, text, video, images, and interactivity to create an engaging, useful, and informative demonstration of the information/tool for future planning. However, it would have been more readable for a person not familiar with the geography of Chicago if it had included some more literal signposting like names of neighborhoods, main streets, and geographic landmarks.

http://www.visualisingdata.com/index.php/2015/01/make-grey-best-friend/

These visualizations serve as an argument for the use of grey as the main color for presentations. The argument follows that grey as a main color allows for sharp contrast in certain colorful areas, drawing the eye to specific, more important data. Also, the author provides images of presentations which employ this method of heavily featuring grey which helps illustrate (literally) their point.

http://www.hyperhistory.com/online_n2/History_n2/a.html

This visualization is an expansive historical database, covering topics grouped into two sets of four categories: science, culture, religion, and politics, and: people, history, events, and maps. Users can view timelines of either important figures lives or events in a particular category. The site color codes the timeline and provides the user with short summaries when clicking a specific piece of data. Though each timeline is useful to a certain extent for getting a sense of a specific time, it is hard to understand the big picture across time periods. Also, the site itself is abrasively web 1.0 in its clunky design and functionality. The most difficult part of the site is that the same information can be accessed through the two different sets of categories. Since the categories are so unclear, it is not always clear exactly where the categorical lines are drawn when it comes to what chart you are looking at.

http://neoformix.com/2013/NovelViews.html

This visualization attempts to analyze Les Miserables by connecting characters to various words in the text, and assessing the frequency and proximity of these words to other words. Though the graphics are consistently aesthetically pleasing, and some are quite simple (like the word clouds), many are almost impossible to understand (like the radial word connections). Also, the descriptions which accompany the the text are often so obtuse and confusing that they lend no clarity to the complex illustrations.

How would you measure their success?  If you had to develop a list of features that make these visualizations successful, what might those include?

I would measure the success of the projects by how clear and engaging the portrayal of the information they attempt to explain is. Though not one of these alone would make a project successful, these features would provide a rubric for grading a successful visualization: clarity, accessibility, interactivity, efficiency in exposition, and depth of analysis.

  1. 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?  

Under “Analyze Data,”  we chose “Timeflow,” an open source timeline which allows journalists to analyze temporal data. It offers several modes to view the data by time, including calendar, timeline, list, and table. The program also allows you to import your own data. “Time Flow” might be useful in analyzing large amounts of data because it does a good job organizing data by time, so if I were working on a project which had a lot of data over a large amount of time, this would be a helpful organizational tool. Under “Visualize Data” I chose “Tableau Public,” which is not an open source web platform, but is free and allows anyone to publish their data visualizations. This would be useful if this were a private project and I could not or did not want to spend my own money. It is also a relatively accessible and usable tool which would help a someone without a coding background visualize a large amount of data. It allows for users to make convenient pivot tables or dashboards to establish an interactive assortment of data.

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