The expansion of isms, 1820-1917: Data-driven analysis of political language in digitized newspaper collections

Abstract

Words with the suffix-ism are reductionist terms that help us navigate complex social issues by using a simple one-word label for them. On the one hand they are often associated with political ideologies, but on the other they are present in many other domains of language, especially culture, science, and religion. This has not always been the case. This paper studies isms in a historical record of digitized newspapers from 1820 to 1917 published in Finland to find out how the language of isms developed historically. We use diachronic word embeddings and affinity propagation clustering to trace how new isms entered the lexicon and how they relate to one another over time. We are able to show how they became more common and entered more and more domains. Still, the uses of isms as traditions for political action and thinking stand out in our analysis.

A data-driven approach to studying changing vocabularies in historical newspaper collections

“…This differs slightly from the original approach in setting the learningrate value of t 1 to that of the end of the previous model (in this case, t 0 ). The aim was to prevent the models from diverging too rapidly, as successfully reported in previous work based on the same data (Hengchen et al, 2019;Pivovarova et al, 2019;Marjanen et al, 2020). These models are referred to later in this article as UPDATE.…”

“…This requires an initial set of seed terms that is subsequently expanded by selecting similar words (Kenter et al, 2015;Recchia et al, 2017). Another approach is to identify a vocabulary based on features of single words such as 'isms' (Pivovarova et al, 2019, Marjanen et al, 2020, or sequences of words (ngrams). The latter approach constructs a vocabulary based on words that are directly preceded (Wevers, 2017;Van Eijnatten and Ros, 2019) or modified (Hill et al, 2018) by a common adjective, and subsequently focuses on the temporal changes.…”

Integrated interdisciplinary workflows for research on historical newspapers: Perspectives from humanities scholars, computer scientists, and librarians

“…However, using these methods requires an understanding of the parameters used (such as frequency thresholds for word types), choosing clustering methods (such as k‐means or affinity propagation) or simply assessing how different algorithms (such Word2Vec or Scot) react to general word type frequency. Choices like these are not only issues for computation, but also have effects for humanities interpretation (Marjanen, Kurunmäki, et al, 2020 ).…”

“…With the advance of digitization and with more elaborate algorithms, tools, and methods developed by computer scientists, digital approaches have started to shape humanities' and especially historians' research, whose goal it is to study the past by exploring, analyzing, interpreting, and contextualizing primary sources such as newspaper articles (Korkeamäki & Kumpulainen, 2019 ; Oberbichler et al, 2020 ). Some historians need to create collections for further qualitative analysis (e.g., Gabrielatos, 2007 ) or use digital tools to support their qualitative research questions (e.g., Brait, 2020 ; Oberbichler, 2020a ; Pfanzelter, 2020 ), some use text mining methods to identify linguistic patterns (Marjanen, Kurunmäki, et al, 2020 ), and others again study geographically distributed phenomena (Borruso, 2008 ).…”

Grasping the Anti-Modern Discourse on Europe in the Swiss Digitised Press, or can Text Mining Generate a Research Corpus from an Article Collection?

“…We would argue that the detected textual overlap and co-occurrences are a stimulating preselection and serve as a grid to manage a large collection of historical source material. Alongside the use of word embeddings to operationalise the conceptual history (Marjanen et al, 2020), the text mining tools can offer a constructive support for the study of discourses. Following-up this initial iteration of creating and adapting research categories to the output of a classifier, and given the difficulty to manually validate the whole corpus, it would be interesting to apply the process to other source materials, for instance, in the context of the impresso collection, to further Swiss newspapers, in order to also include socialist titles and Luxembourgish newspapers of the time.…”