Cultural Cartography with Word Embeddings
This work addresses the need for more nuanced text analysis in sociology and cultural studies, offering a method to study cultural phenomena like immigration discourse, but it is incremental as it applies existing word embedding techniques to new theoretical contexts.
The paper tackles the problem of analyzing text by moving beyond keyword frequency to capture relational word meanings, using word embeddings to map cultural discourse and demonstrate strategies for interpreting cultural theory topics like social marking and echo chambers.
Using the frequency of keywords is a classic approach in the formal analysis of text, but has the drawback of glossing over the relationality of word meanings. Word embedding models overcome this problem by constructing a standardized and continuous "meaning space" where words are assigned a location based on relations of similarity to other words based on how they are used in natural language samples. We show how word embeddings are commensurate with prevailing theories of meaning in sociology and can be put to the task of interpretation via two kinds of navigation. First, one can hold terms constant and measure how the embedding space moves around them--much like astronomers measured the changing of celestial bodies with the seasons. Second, one can also hold the embedding space constant and see how documents or authors move relative to it--just as ships use the stars on a given night to determine their location. Using the empirical case of immigration discourse in the United States, we demonstrate the merits of these two broad strategies for advancing important topics in cultural theory, including social marking, media fields, echo chambers, and cultural diffusion and change more broadly.