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This Digital Humanities Quarterly article discusses probabilistic text mining as a way to learn about social interactions from Britain in the early-modern period—around the 16 th and 17 th century. Researchers developed a model (or matrix) that creates a map of relationships between individuals that are
referred to in scholarly texts. This is interesting because it lies at the intersection of computer
science and the humanities. In the fifth section, “Humanities Significance,” it is noted that
while humanists care about documentary evidence of connections between people, they would need to do such an unbelievable amount of research to develop a map like the one this model produces. Thus, while this is not perfect, it can definitely be used to get a sense of social networks. And moving forward, the opportunities are profound. Models like this can be used to study social networks in other places—all that is needed “is machine-readable text in which the concurrence of names is a reasonable indicator
of connections between persons.” It is truly amazing how groups can identify source texts that can be used as evidence of historical relationships to then serve as the material for network analysis. We see in the reading how marriage certificates, archival letters—any type of document that historians could use to link individuals together are used. For our work in DCS 104, the relationships among mill workers, their families, and their community can be used by looking at address data.