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.
翻译:错误信息和群体间偏向是挑战知情公民的两个病理。本文审视了在中国数字公共领域有争议科学的错误信息中如何使用身份语言,并揭开关于争议性科学的信息,以及这些语言对公众如何与科学互动的影响。我们收集了中国流行的 ⁇ A平台Zhihu(Zhihu)关于最有争议的科学问题的八年时间系列公开讨论数据集(N=6039)。我们发现,在讨论有争议的科学问题时,错误信息和被揭开的信息都使用大量群体身份语言,而我们将其定义为科学派别主义,关于科学的讨论则由科学态度形成的派别分裂开来。我们发现,使用科学派别主义的文章获得更多的数字投票和评论,即使是在中国科学流传社区中也是如此。科学派别主义也增加了公共讨论对否定性的使用。我们讨论了科学派别主义如何与数字关注经济互动的影响,以影响公众与科学误传。