Salem Witch Trials network analysis
Using the digitized Salem Witchcraft Papers, students will identify and create a network analysis of the persons involved in the Salem witchcraft trials of 1692.
Overview
Students will begin this scaffolded project by annotating the Bridget Bishop trial transcripts, which have been scanned and transcribed at the Salem Witch Trials Documentary Archive. This close reading of the sources will prepare them for the next assignment, a short essay—What Makes a Witch.
In this assignment, students choose an accused witch from the Salem trials and—using the transcribed court records—identify what neighbors said about the individual that made them a so-called witch and how the accused witch attempted to defend him or herself.
Now that they’re more comfortable with the transcripts themselves, the assignment moves on to a network analysis of the persons involved in the Salem witch trials.
Students will get experience using Palladio, first using a set of data I’ve already compiled on Bridget Bishop. This will serve as their example data.
Students will then be assigned a specific individual (it might be a team effort for some accused witches for whom there are quite a few documents). Their task is to document each person named in the documents and how that person was connected to the accused witch. Were they the ones who made the accusation? Were they accused of witchcraft in the same document? Were they mentioned as someone who was injured by the accused witch?
Other information such as gender, residence (Salem Village vs. Salem Town), will also be recorded as network attributes.
Each student will be responsible for implementing the data they’ve collected into Palladio to create an accused-witch specific network cluster.
Finally, I will merge all the data together to create a master network out of which deeper analysis and observations can be made to answer questions such as:
Who was most central to the Salem Witch Trials?
Was there a correlation between geography? Gender? Age?
In this assignment, students choose an accused witch from the Salem trials and—using the transcribed court records—identify what neighbors said about the individual that made them a so-called witch and how the accused witch attempted to defend him or herself.
Now that they’re more comfortable with the transcripts themselves, the assignment moves on to a network analysis of the persons involved in the Salem witch trials.
Students will get experience using Palladio, first using a set of data I’ve already compiled on Bridget Bishop. This will serve as their example data.
Students will then be assigned a specific individual (it might be a team effort for some accused witches for whom there are quite a few documents). Their task is to document each person named in the documents and how that person was connected to the accused witch. Were they the ones who made the accusation? Were they accused of witchcraft in the same document? Were they mentioned as someone who was injured by the accused witch?
Other information such as gender, residence (Salem Village vs. Salem Town), will also be recorded as network attributes.
Each student will be responsible for implementing the data they’ve collected into Palladio to create an accused-witch specific network cluster.
Finally, I will merge all the data together to create a master network out of which deeper analysis and observations can be made to answer questions such as:
Who was most central to the Salem Witch Trials?
Was there a correlation between geography? Gender? Age?
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HST225 Salem Witch Trials, Fall 2017
Notes
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Outcome summary
Students had a hard time signing up for an Annotation Studio account and linking to the sample trial transcripts I'd posted there. It took much longer in-class time to get everyone on the same page. In the future I'll consider using Google Docs since students are more familiar with this platform and it serves the same function. Most students were able to annotate the documents with fair accuracy. The "What Makes a Witch" papers that resulted from this were far stronger than when I've previously assigned this small paper without first having them annotate court transcripts.
I'm hopeful students found the value in collecting data for future classes/scholarship. Some students were far more thorough in their data mining than others. Most were able to follow my instructions regarding formatting and what numbers represent what relationships/categories, although I did have to go back through the data to standardize the spelling of certain names. There's also the problem that some individuals are Senior and Junior and if the document did not designate to which person they were referring, it's a challenge to identify if it's, for example, Ann Putnam Jr. or Ann Putnam Sr.
It's a very impressive first step in data collection; I'll need to have future classes double-check the work of the students that came before them before I'm able to confidently use the data for publishable scholarship.
I'm hopeful students found the value in collecting data for future classes/scholarship. Some students were far more thorough in their data mining than others. Most were able to follow my instructions regarding formatting and what numbers represent what relationships/categories, although I did have to go back through the data to standardize the spelling of certain names. There's also the problem that some individuals are Senior and Junior and if the document did not designate to which person they were referring, it's a challenge to identify if it's, for example, Ann Putnam Jr. or Ann Putnam Sr.
It's a very impressive first step in data collection; I'll need to have future classes double-check the work of the students that came before them before I'm able to confidently use the data for publishable scholarship.
Materials
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