# Generating Timelines by Modeling Semantic Change

arXiv: https://arxiv.org/abs/1909.09907 · HTML: https://mlsanity.com/paper/1909.09907/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 21 Sep 2019.

## Built on by (most cited first, 2 of 2)

- [Simple, Interpretable and Stable Method for Detecting Words with Usage Change across Corpora](https://mlsanity.com/paper/2112.14330/) (2021)
- [Change Summarization of Diachronic Scholarly Paper Collections by Semantic Evolution Analysis](https://mlsanity.com/paper/2112.03634/) (2021)

## Abstract (arXiv)

Though languages can evolve slowly, they can also react strongly to dramatic world events. By studying the connection between words and events, it is possible to identify which events change our vocabulary and in what way. In this work, we tackle the task of creating timelines - records of historical "turning points", represented by either words or events, to understand the dynamics of a target word. Our approach identifies these points by leveraging both static and time-varying word embeddings to measure the influence of words and events. In addition to quantifying changes, we show how our technique can help isolate semantic changes. Our qualitative and quantitative evaluations show that we are able to capture this semantic change and event influence.