AI 中文总结
研究追踪2026年伊朗战争中特朗普声明在不同平台的转移，用度量到语义链接框架和数据集，探究平台架构对地缘政治冲突下游白话的影响，揭示不同平台信息传播差异及原因，推进多平台比较设计在计算政治传播中的应用。
AI 中文摘要
随着高风险的行政危机沟通转向碎片化的数字生态系统，未经调解的叙事越来越多地在封闭广播飞地内产生，然后扩散到结构不同的开放网络中。然而，跨平台信息迁移的机制仍缺乏理论支持，这凸显了系统计算分析的必要性。本研究追踪了特朗普总统在2026年伊朗战争期间的声明从Truth Social转移到X-Twitter和Bluesky的转变。使用度量到语义链接框架和9891个时间对齐的公众回应的高通量数据集，我们研究了不同的平台架构如何塑造地缘政治冲突的下游白话。结果揭示了由社会技术能力驱动的明显行为差异。在X-Twitter上，话语由结构性信息瓶颈主导：来自精英代理节点的病毒式转发级联压缩了词汇多样性并集中了解释性框架，单个级联占子语料库的55.8%。相比之下，去中心化的Bluesky AT协议支持分布式、多声音的评论，其特点是在危机事件中进行分析性超脱和比例关注。这些模式不仅源于架构决定论，还源于平台能力与本地化用户人口统计之间的相互作用。通过将宏观参与度量与下游语义框架解耦，本研究推进了计算政治传播中多平台比较设计的案例。
英文摘要
As high-stakes executive crisis communication shifts into fragmented digital ecosystems, unmediated narratives increasingly originate within closed-broadcast enclaves before diffusing into structurally distinct open networks. Yet the mechanisms governing cross-platform information migration remain under-theorized, underscoring the need for systematic computational analysis. This study tracks the transformation of President Trump's statements during the 2026 Iran War as they move from Truth Social into X-Twitter and Bluesky. Using a Metric-to-Semantic-Linkage framework and a high-throughput dataset of 9,891 temporally aligned public responses, we examine how divergent platform architectures shape the downstream vernacular of geopolitical conflict. The results reveal pronounced behavioral divergence driven by sociotechnical affordances. On X-Twitter, discourse is dominated by structural information bottlenecks: viral retweet cascades from elite proxy nodes compress lexical diversity and centralize interpretive framing, with a single cascade accounting for 55.8 percent of the sub-corpus. In contrast, the decentralized Bluesky AT Protocol supports distributed, multi-vocal commentary marked by analytical detachment and proportional attention across crisis events. These patterns arise not from architectural determinism alone but from the interaction between platform affordances and localized user demographics. By operationalizing the decoupling of macro-engagement metrics from downstream semantic framing, this study advances the case for multi-platform comparative designs in computational political communication.
Comments28 pages, 1 figure, 2 tables, research article
