A workflow will run and generate the visualization files in a different repository, so to see the final visualization, visit this website.

This repository contains the source code but the most recent "compiled" network-app is located in the drag-network repository. The easiest thing is therefore to

$ git clone https://github.com/kallewesterling/drag-network

Since you are cloning the drag-network repository, you do not need to process the dataset as it already comes with the latest updated one.

To run the analysis, clone this package and run in your terminal:

$ python generate-cooccurrence-data.py

Navigate into the cloned directory:

$ cd drag-network

Then open a local HTTP server:

$ python -m http.server

Note that this will only work on Python 3.

Kalle Westerling is a Ph.D. Candidate in Theatre and Performance at The Graduate Center, CUNY, where he works on a dissertation about the history and aesthetics of male-identified bodies in 20th-century burlesque and 21st-century boylesque. He is also the project manager for the NEH-funded project “Expanding Communities of Practice,” aimed at helping to create infrastructure for digital humanities across several higher education institutions across the U.S. Read more about Kalle Westerling on his website.

The dataset was created in a combination of a manual and automatic process, where searches were performed across a number of databases, results collated and PDF files/images of scanned newspapers were presented to the researcher (see below), who then manually coded all of the data into a data row for each person who occurred on that particular data in that particular newspaper.

The dataset can be seen here.

The data was manually processed into each column of each row as follows.

Each row has some central data assigned to it, which includes:

• a date (in the format YYYY-MM-DD)
• a name of the performer
• a name of the venue
• if not venue is mentioned but a city is mentioned, that name is filled out as well
• a source

Optional data includes:

• If there is a revue name mentioned, it is also noted here.
• If there is a legal name mentioned for the given performer, the legal name is noted
• If there is an alleged age mentioned for the given performer, the alleged age (and consequentially, the assumed birth year) are noted
• ID number that identifies the source in the Entertainment Industry Magazine Archive (EIMA)
• How the source was found through a search in newspapers.com
• How the source was found through a search in Fulton archives
• How the source was found through a search in an already existing archive
• Edge comment, which refers to any comments on the source itself (meta)
• Whether the data point shall be excluded from the final visualization
• Any interesting quotes from source
• Any interesting comments on the performer
• Any interesting comments on the venue
• Any interesting comments on the city
• Any interesting comments on the revue

Cleaned up data includes:

• Name of the performer
• Name of the venue
• Name of the city
• Source