Mapping the Republic of Letters: Benjamin Franklin’s Papers

The Republic of Letters is a massive project that looks at the correspondence of different historic figures throughout time, anywhere from Galileo to Benjamin Franklin. I chose to focus on the circulation of Benjamin Franklin’s papers throughout Europe (from 1757-1775) found here as it was an interesting and mostly complete data set. In the article the nodes of the graph are locations that Franklin’s letters and papers were sent from or arrived at, with varying size of nodes depending on the quantity of correspondence. The edges are the precise papers/letters that were sent from those locations with authorship and date included where available. Interestingly enough, this project was created in Palladio, a tool we learned about in class! It’s super cool to see something we experimented with during class applied to a large project like this one. In fact, many of the other publications that the Republic of Letters has made have visualizations in Palladio.

Republic of Letters Infographic depicting authors, time span and important figures

The Franklin project was created by scouring the Franklin Papers’ database for letters and papers sent in this time period, uploading the data set to Palladio then doing some exploration of the data with the tools we saw in class. This publication is very much an exploratory analysis of this data as there is no real claim being provided, only interesting information. I would love to see what someone can do with this type of data – are there particular people that show up more often in this network? Why or why not? Are there important figures of the era that are not included at all? All these questions could potentially be answered by exploring this data and looking for deeper connections.



  1. This project uses a very creative form of network that’s different from ordinary networks that has dotted nodes and lines as edges. I like how this project uses pictures of the figures as the nodes. Very creative.

  2. One thing I’ve struggled with in interpreting these networks is the spatiality of the connections. Often it seems completely arbitrary how far two nodes are away from each other (nodes can even be stretched and pulled around in some cases).
    Thus, I enjoyed the fact that this network was presented on a geographic map. This gives more information about the nature of the edges which makes it easier to conceptualize.

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