Recovering Women’s History with Network Analysis: A Case Study of the Fabian News

Literary study in the digital humanities is not exempt from reproducing historical hierarchies by focusing on major or canonical figures who have already been recognized as important historical or literary figures. However, network analysis of periodical publications may offer an alternative to the biases of human memory, where one has the tendency to pay attention to a recognizable name, rather than one that has had no historical significance. It thus enables researchers to see connections and a wealth of data that has been obscured by traditional recovery methodologies. Machine reading with network analysis can therefore contribute to an alternate understanding of women’s history, one that reinterprets cultural and literary histories that tend to reconstruct gender-based biases. This paper uses network analysis to explore the Fabian News, a late nineteenth-century periodical newsletter produced by the socialist Fabian Society, to recover women activists committed to social and political equality.