发表机构
Independent Researcher
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
本研究利用LLM分析2026年孟加拉国麻疹暴发报道，发现媒体显著放大威胁但克制归责，提供可扩展的LMIC疫情媒体分析方法。
AI 中文摘要
新闻媒体如何构建公共卫生紧急事件的框架并对其进行情感编码，会影响公众的风险感知和信任，然而针对低收入和中等收入国家（LMICs）的疫情报道动态仍研究不足。我们考察了孟加拉国英文媒体对2026年麻疹暴发报道中的情感和立场——这是该国二十年来最严重的疫情，在64个县中的61个县报告了超过97,000例疑似病例和600例死亡，发生在2024年政府更迭和2024-2025年疫苗缺货之后。利用互联网档案馆（Internet Archive），我们构建了一个可复现的语料库，包含来自七家全国性媒体的403条标题（其中2026年内396条），使用大型语言模型在锁定编码手册下对二元情感和四向立场进行标注，并与两名编码员人工裁决的金标准（n=153；Cohen's kappa=0.89立场，0.75情感）进行验证。与DGHS流行病曲线对齐，报道的负面程度显著增加（负面比例从56%升至88%；Cochran-Armitage z=4.12，p<.001），风险放大框架强化（从44%升至84%；z=4.15，p<.001）。媒体负面情绪滞后于发病率，追踪累积死亡率。与政治背景相反，归责仍然是小众框架（总体约9%），且绝大多数是系统性归责（37例中32例，86%），而非针对具名行为者。该流程为LMIC疫情媒体分析提供了一种可扩展、透明的方法；孟加拉国报道对威胁的放大远多于对政治责任的归咎。
英文摘要
How news media frame and emotionally code a public health emergency shapes public risk perception and trust, yet outbreak-coverage dynamics remain understudied for low- and middle-income countries (LMICs). We examine sentiment and stance in English-language Bangladeshi coverage of the 2026 measles outbreak -- the country's most severe in two decades, with over 97,000 suspected cases and 600 deaths across 61 of 64 districts, unfolding after the 2024 change of government and a 2024-2025 vaccine stockout. Using the Internet Archive, we build a reproducible corpus of 403 headlines from seven national outlets (396 in-window in 2026), label them for binary sentiment and four-way stance via a large language model under a locked codebook, and validate against a two-coder human-adjudicated gold standard (n=153; Cohen's kappa=0.89 stance, 0.75 sentiment). Aligned to the DGHS epidemic curve, coverage grew significantly more negative (56% to 88% negative; Cochran-Armitage z=4.12, p<.001) and risk-amplification framing intensified (44% to 84%; z=4.15, p<.001). Media negativity lagged incidence, tracking cumulative mortality. Contrary to the political backdrop, blame remained a minority frame (~9% overall) and was overwhelmingly systemic (32 of 37, 86%) rather than directed at named actors. The pipeline offers a scalable, transparent method for LMIC outbreak-media analysis; Bangladeshi coverage amplified threat far more than it assigned political blame.
Comments10 pages, 2 figures
