Abstract
ABSTRACT This article introduces a data-intensive approach to visualizing political ideologies as text networks. The methodology combines network theory with collocation analysis from corpus linguistics. Its similarities and differences to Michael Freeden’s morphological approach are highlighted. The prospects are examined by focusing on the case study of Finnish socialism in the early 20th century. Primary sources consist of printed labor newspapers, handwritten newspapers produced by ordinary working people, and parliamentary speeches. The empirical part demonstrates that the network approach is useful for (1) locating key political words based on centrality in the network, (2) identifying clusters of words related to each other more strongly than to the rest of the network, and (3) seeing the structure of an ideological network. The main contribution of the article is methodological for the approach can be applied to other machine-readable sources, both at small and large scales, to automatically extract information on the linguistic patterns characteristic of a political ideology under investigation.
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