The 2024 Bluebird Movement in Taiwan marked one of the largest youth-led protests in the country's democratic history, mobilizing over 100,000 demonstrators in response to parliamentary reforms. Unlike the 2014 Sunflower Movement, Bluebird unfolded within a transformed digital environment dominated by Threads, Meta's new microblogging platform that uniquely draws 24% of its global traffic from Taiwan. Leveraging a dataset of 62,321 posts and 21,572 images, this study analyzes how protest communication developed across textual and visual modalities. We combine LLM zero-shot annotation, gradient-boosting trees, and SHAP explainers to disambiguate the supply and demand of attention. Results reveal three dynamics: (1) partisan asymmetries between algorithmic exposure and user endorsement, with anti-DPP content surfaced more widely but anti-KMT and pro-DPP content more actively recirculated; (2) textual repertoires centered on commemorations, personal testimonies, and calls to action as key drivers of virality; and (3) a bifurcation in visual strategies, where human photographs concentrated exposure and discussion, while AI-generated animal and plant symbols circulated as mobilization tools and partisan attacks. These findings demonstrate how Threads functioned as both an amplifier and filter of democratic contention, extending theories of emotional and visual contagion by showing how generative AI reshapes symbolic repertoires in contemporary protest through what we term kawaii toxicity, political attacks cloaked in aesthetics of cuteness.

翻译：2024年台湾蓝鸟运动是该国民主历史上规模最大的青年主导抗议活动之一，因应议会改革动员超过10万名示威者。与2014年太阳花运动不同，蓝鸟运动在由Threads主导的转型数字环境中展开——这款Meta旗下新型微博平台独特的全球流量有24%来自台湾。基于62,321条帖子和21,572张图像的数据集，本研究分析了抗议传播如何在文本与视觉模态中发展。我们结合大语言模型零样本注释、梯度提升树与SHAP解释器，厘清注意力的供需关系。结果揭示了三种动态：(1)算法曝光与用户认可之间的党派不对称性——反民进党内容更广泛传播，而反国民党和亲民进党内容被更积极转发；(2)以纪念、个人证词和行动号召为核心的文本库成为病毒式传播的关键驱动因素；(3)视觉策略呈现二元分化——人物照片集中了曝光与讨论，而AI生成的动植物符号则作为动员工具和党派攻击手段传播。这些发现表明Threads同时充当了民主抗争的放大器与过滤器，通过我们称之为“卡哇伊毒性”（以可爱美学包裹的政治攻击）的概念，拓展了情感与视觉传染理论，揭示了生成式AI如何重塑当代抗议中的符号库。