For my network analysis of DH projects, I decided to use “Palladio” to visualize ads. The project I chose focuses on visualizing the paths of runaway slaves that were collected from jailers’ notices. The publishers of this project were only able to extract some data from a few states, such as Mississippi, Arkansas, and Texas, between the years 1840-1842. They were only able to obtain data from one county jail from each state, namely Jefferson County (MS), Pulaski County (AR), and Bexar County (TX).
Scholarship on fugitive slaves identified several geographic trends in the directions taken by runaways. It was found that some slaves temporarily “laid out” in the vicinity of their owners’ farms or plantations, while others ran farther with the intent to stay with relatives or to reach freedom. Franklin and Schweninger’s research found that “slaves living in the Lower Mississippi River Valley or Mississippi and Alabama were more likely to run south and west than north,” making Texas and Mexico possible destinations for runaway slaves (Franklin and Schweninger, 112).
Although they generally couldn’t tell which routes runaway slaves took to get to their destinations, simply connecting points between their start locations and where they were captured gave them an idea about where they were heading.
What (or who) are the nodes and what are the edges?
The nodes represent the locations where the owners’ homes were situated, from which the slaves fled. They also represent the destination of the slaves who were captured and taken to county jails. The edges on the map depict the possible routes that the slaves might have taken to reach the locations where they were captured.
How was the project created?
The creators of this particular project utilized two sets of jailers’ notices from each state to collect geographic data. They manually entered this data into a spreadsheet, which stored information on the owner’s location as reported by the slave, as well as the location of the county jail where the runaway was held after being captured.
Afterward, they uploaded their data to Palladio to visualize it. By merging the “from” and “to” locations with geographic coordinates, they were able to create visualizations of the data. They chose the “Point to Point” option for the map type to represent the directions taken by runaway slaves. By creating separate maps for each state, they were able to conclude differences in runaway patterns across the South.
Before working with data from jailers’ notices from each state, they originally did some close reading of runaway slave advertisements from different states. However, they faced some limitations in finding patterns by simply reading through a corpus of runaway slave advertisements. While close reading was beneficial, it wasn’t enough to uncover all the details they needed.
6 thoughts on “Network Analysis – Using Palladio to Visualize ADS”
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This is a very interesting project that provides a spatial dimension to our understanding of slave history. And I agree with you that the details are not being adequately presented. I think it would be better if this project could determine the specific routes of slave escapes based on more historical clues, perhaps leading to more discoveries, rather than simply connecting two points.
Yes, I totally agree with you on the idea of a better representation of our maps. But we don’t have all that data available to us at the moment and there isn’t an efficient way to sparse data from sources like corpse readings and advertisements.
Great work on analyzing the project, I think that the project is super important because it helps us better understand slave history. It seems interesting to me that the data used was manually entered, which seems highly inconvenient. It is also interesting that you pointed out their first approach to analyzing old ads. Do you think there is a better way to do this project? I also agree with your nodes and edges analysis.
At the moment we don’t have many resources that can help us sparse the data from the large amount of readings or ads/jailers’ notices. But, I do believe that if we can digitize all of our data including the readings, ads, etc… we can build programs that can turn key words into data files such as a csv and then use PostgreSQL to sparse and separate the data. Then, we can feed it into these software where we can then visualize it.
Wow this project is super cool and you did a really good job analyzing it! I thought it was really interesting that they were using primary sources to map this. Also their choice of “point to point” really helped me understand the movement these runaway slaves took across the country.
Thank you, Sydney! I completely agree with you that the “point to point” option is intriguing. However, I think it would have been even more useful if they had included an arrow indicating the direction of travel. Without it, users would have to rely solely on their own analysis to determine where they’re headed. OR maybe they just did that intentionally to encourage exploration and discovery of the users??!