# AI-based approach to burnout identification from textual data

arXiv: https://arxiv.org/abs/2601.17993 · HTML: https://mlsanity.com/paper/2601.17993/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- First posted on arXiv 25 Jan 2026.

## Abstract (arXiv)

This study introduces an AI-based methodology that utilizes natural language processing (NLP) to detect burnout from textual data. The approach relies on a RuBERT model originally trained for sentiment analysis and subsequently fine-tuned for burnout detection using two data sources: synthetic sentences generated with ChatGPT and user comments collected from Russian YouTube videos about burnout. The resulting model assigns a burnout probability to input texts and can be applied to process large volumes of written communication for monitoring burnout-related language signals in high-stress work environments.