This Digital Humanities Quarterly article discusses probabilistic text mining as a way to learn about social interactions from\u00a0Britain in the early-modern period\u2014around the 16 th and 17 th century. Researchers\u00a0developed a model (or matrix) that creates a map of relationships between individuals that are
\nreferred to in scholarly texts. This is interesting because it lies at the intersection of computer
\nscience and the humanities. In the fifth section, \u201cHumanities Significance,\u201d it is noted that
\nwhile humanists care about documentary evidence of\u00a0connections between people, they would need to do such an unbelievable amount of research\u00a0to develop a map like the one this model produces. Thus, while this is not perfect, it can\u00a0definitely be used to get a sense of social networks. And moving forward, the opportunities are\u00a0profound. Models like this can be used to study social networks in other places\u2014all that is\u00a0needed \u201cis machine-readable text in which the concurrence of names is a reasonable indicator
\nof connections between persons.\u201d It is truly amazing how groups can identify source texts that can be used as evidence of\u00a0historical relationships to then serve as the material for network analysis.\u00a0We see in the reading how marriage certificates, archival letters\u2014any type of\u00a0document 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.<\/p>\n","protected":false},"excerpt":{"rendered":"

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