AI-inferred expressed well-being and collective-action discourse in climate-change campaigns on X
AI-inferred expressed well-being and collective-action discourse in climate-change campaigns on X
基于人工智能推断的 X 平台气候变化运动中的幸福感表达与集体行动话语
Abstract: Climate campaigns are often evaluated through attention and mobilization, but less is known about the well-being language that accompanies them. Whether campaign periods alter positive affect and hope, and whether happiness aligns with action language, remains unresolved.
摘要： 气候运动的评估通常侧重于关注度和动员力，但人们对其伴随的幸福感语言知之甚少。运动期间是否会改变积极情感和希望，以及幸福感是否与行动语言相一致，目前尚无定论。
We analysed 364,118 public Twitter/X posts from Earth Day, Earth Hour, Global Climate Action Day and World Environment Day in 19 occurrence-years, using 30-day pre-event, event and post-event windows. A versioned weighted lexical model estimated happiness, future-oriented hope, collective capability, distress and action language.
我们分析了 19 年间地球日、地球一小时、全球气候行动日和世界环境日期间的 364,118 条 Twitter/X 公开帖文，并采用了活动前、活动中及活动后各 30 天的时间窗口。研究利用版本化加权词汇模型，评估了幸福感、面向未来的希望、集体能力、痛苦感和行动语言。
Event-period happiness prevalence was 9.02 percentage points higher than the pre-event baseline, whereas paired occurrence contrasts showed a 10.75-point decline in action language, indicating a happiness—action divergence. The happiness estimate remained positive across composition and text-deduplication checks, but was less precise under a 19-cluster wild bootstrap. Happier source posts had lower odds of an observed matched retweet cascade.
活动期间的幸福感普及率比活动前基准高出 9.02 个百分点，而配对事件对比显示行动语言下降了 10.75 个百分点，这表明幸福感与行动之间存在背离。在经过文本构成和去重检查后，幸福感评估结果依然呈正向，但在 19 簇野引导（wild bootstrap）检验下精确度有所下降。研究还发现，幸福感较高的原始帖文引发匹配转发浪潮的概率较低。
Subjects: Computation and Language (cs.CL); Computers and Society (cs.CY) 学科分类： 计算与语言 (cs.CL)；计算机与社会 (cs.CY)