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The goal of this article is twofold. On the one hand I want to outline the main topics, themes and trends of the past 123 (at the time of writing) issues of Russian Literature and shed some light on the journal’s main subject areas. On the other hand, I show how ‘traditional’ topic modeling visualizations such as topic distributions per document, word distributions per topic, and time series of topic distributions, can be complemented by novel approaches such as the topic map, which significantly facilitates the interpretation of the corpus structure and document similarities. Moreover, topic maps reduce the need to make sense of individual topics and allow the researcher to focus directly on the texts themselves and on the corpus as a whole. |
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