Public Perception Towards Intelligent Medical Technologies During and Post COVID-19 Pandemic: Exploring Health Communication in Social Media using Neural Topic Models

Previous research has demonstrated that individuals possess both expectations and concerns regarding the impact of emerging intelligent medical technologies. Notably, during the COVID-19 pandemic, the implementation of such technologies played a crucial role in combating the virus. As society transitions into a new normal, the rapid advancements of large language models have sparked an intensified debate concerning ChatGPT-based medical applications. In this context of public healthcare events and the resurgence of artificial intelligence, it becomes imperative to reevaluate public attitudes and opinions towards intelligent medical technologies. This paper seeks to update the prevailing public perception of intelligent medical technologies during and after the COVID-19 pandemic. To achieve this, we conduct an analysis of tweets related to intelligent medical technologies within a specific timeframe using BERTopic, a neural topic modeling technique. As topic modeling has proven effective in gauging social psychological characteristics on social media, our findings indicate a notable surge in discussions concerning intelligent medical technologies during the post COVID-19 period, with a particular emphasis on ethical and risk-related issues associated with ChatGPT-based medical applications. This work demonstrates that topic modeling serves as a suitable tool in computational social psychology for capturing collective perceptions at the group-level.