Science Factionalism: How Group Identity Language Affects Public Engagement with Misinformation and Debunking Narratives on a Popular Q&A Platform in China

TL;DR

This study analyzes how group identity language influences public engagement with science misinformation and debunking on a Chinese Q&A platform, revealing that factionalism increases engagement and negativity in discussions.

Contribution

It introduces the concept of science factionalism in digital discourse and demonstrates its impact on public engagement with science misinformation in China.

Findings

Both misinformation and debunking use substantial identity language.

Posts with factionalism receive more votes and comments.

Factionalism increases negativity in public discourse.

Abstract

Misinformation and intergroup bias are two pathologies challenging informed citizenship. This paper examines how identity language is used in misinformation and debunking messages about controversial science on Chinese digital public sphere, and their impact on how the public engage with science. We collected an eight-year time series dataset of public discussion (N=6039) on one of the most controversial science issues in China (GMO) from a popular Q&A platform, Zhihu. We found that both misinformation and debunking messages use a substantial amount of group identity languages when discussing the controversial science issue, which we define as science factionalism -- discussion about science is divided by factions that are formed upon science attitudes. We found that posts that use science factionalism receive more digital votes and comments, even among the science-savvy community in China. Science factionalism also increases the use of negativity in public discourse. We discussed the implications of how science factionalism interacts with the digital attention economy to affect public engagement with science misinformation.