Perception and argumentation in the LK-99 superconductivity controversy: a sentiment and argument mining analysis - Eunhye Kim; Wei Luo; Hunkoog Jho (Scientific Reports)
Abstract The announcement of LK-99 as a potential room-temperature, ambient-pressure superconductor sparked widespread debate across both traditional news outlets and social media platforms. This study investigates public perceptions and argumentation patterns surrounding LK-99 by applying sentiment analysis and computational argument mining to a diverse dataset. We analyzed 797 YouTube videos, 71,096 comments, and 1,329 news articles collected between 2023 and 2024. Our results reveal distinct sentiment trajectories: while news articles and YouTube posts exhibit fluctuating yet predominantly positive tones, user comments consistently maintain a more negative sentiment. Discourse analysis shows that structured argumentation—especially reasoning based on expert opinions, observable signs, and anticipated consequences—is prevalent in professionally curated content, whereas a significant proportion of user comments lack identifiable argumentation schemes. Moreover, channel-level analysis indicates that non-expert channels, despite their limited specialization in science, attract higher audience engagement than traditional science channels. These findings highlight the complexities of digital science communication and underscore the need for adaptive strategies that bridge the gap between expert evidence and public discourse. Our study provides practical recommendations to enhance public understanding of scientific advancements in digital spaces.