Political and social topics show measurable semantic drift in online discourse over time, detectable through embedding-space analysis—a technique that could help track how language and meaning evolve around contentious issues.
This paper analyzes how topics shift and evolve in Reddit discussions over 16 years by tracking semantic embeddings of 12.7 billion comments. Using pretrained language models and unsupervised clustering, the researchers show that politically charged topics drift significantly in meaning over time, while stable domains like sports remain consistent.