# Cultural Cartography with Word Embeddings

arXiv: https://arxiv.org/abs/2007.04508 · HTML: https://mlsanity.com/paper/2007.04508/

## Key facts

- Cited by 7 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 9 Jul 2020.

## Built on by (most cited first, 7 of 7)

- [Computational Hermeneutics: Evaluating generative AI as a cultural technology](https://mlsanity.com/paper/2604.16403/) (2026)
- [Theoretical foundations and limits of word embeddings: what types of meaning can they capture?](https://mlsanity.com/paper/2107.10413/) (2021)
- [Adjusting Interpretable Dimensions in Embedding Space with Human Judgments](https://mlsanity.com/paper/2404.02619/) (2024)
- [Probabilistic Embeddings with Laplacian Graph Priors](https://mlsanity.com/paper/2204.01846/) (2022)
- [The Differential Meaning of Models: A Framework for Analyzing the Structural Consequences of Semantic Modeling Decisions](https://mlsanity.com/paper/2509.00248/) (2025)
- [ASTRA: Mapping Art-Technology Institutions via Conceptual Axes, Text Embeddings, and Unsupervised Clustering](https://mlsanity.com/paper/2603.28816/) (2026)
- [Method, Mind, and Morality: How People Make Sense of Artificial Intelligence](https://mlsanity.com/paper/2608.24748/) (2026)

## Abstract (arXiv)

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.