# Measuring the Semantic Structure and Evolution of Conspiracy Theories

arXiv: https://arxiv.org/abs/2603.26062 · HTML: https://mlsanity.com/paper/2603.26062/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 9 of its 55 references that are in the map.
- First posted on arXiv 27 Mar 2026.

## Builds on (most cited first, 9 of 9)

- [Efficient Estimation of Word Representations in Vector Space](https://mlsanity.com/paper/1301.3781/) (2013)
- [Diachronic Word Embeddings Reveal Statistical Laws of Semantic Change](https://mlsanity.com/paper/1605.09096/) (2016)
- [Statistically Significant Detection of Linguistic Change](https://mlsanity.com/paper/1411.3315/) (2014)
- [Simple, Interpretable and Stable Method for Detecting Words with Usage Change across Corpora](https://mlsanity.com/paper/2112.14330/) (2021)
- [Interpretable Word Sense Representations via Definition Generation: The Case of Semantic Change Analysis](https://mlsanity.com/paper/2305.11993/) (2023)
- [A Golden Age: Conspiracy Theories' Relationship with Misinformation Outlets, News Media, and the Wider Internet](https://mlsanity.com/paper/2301.10880/) (2023)
- [Trend of Narratives in the Age of Misinformation](https://mlsanity.com/paper/1504.05163/) (2015)
- [Style Matters! Investigating Linguistic Style in Online Communities](https://mlsanity.com/paper/2209.13114/) (2022)
- [Events and Controversies: Influences of a Shocking News Event on Information Seeking](https://mlsanity.com/paper/1405.1486/) (2014)

## Abstract (arXiv)

Research on conspiracy theories has largely focused on belief formation, exposure, and diffusion, while paying less attention to how their meanings change over time. This gap persists partly because conspiracy-related terms are often treated as stable lexical markers, making it difficult to separate genuine semantic changes from surface-level vocabulary changes. In this paper, we measure the semantic structure and evolution of conspiracy theories in online political discourse. Using 169.9M comments from Reddit's r/politics subreddit spanning 2012--2022, we first demonstrate that conspiracy-related language forms coherent and semantically distinguishable regions of language space, allowing conspiracy theories to be treated as semantic objects. We then track how these objects evolve over time using aligned word embeddings, enabling comparisons of semantic neighborhoods across periods. Our analysis reveals that conspiracy theories evolve non-uniformly, exhibiting patterns of semantic stability, expansion, contraction, and replacement that are not captured by keyword-based approaches alone.