2023/12/04 by Benjamin Litterer, David Jurgens, Litterer, Benjamin +3
Social Sciences · #Computation and Language (cs.CL) #Computational and Text Analysis Methods #Computers and Society (cs.CY) #FOS: Computer and information sciences #Media Influence and Politics #Media Studies and Communication #Social and Information Networks (cs.SI)
paper · pdf · doi:10.48550/arxiv.2312.02118
openalex publication_date 2023/12/04 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
Most events in the world receive at most brief coverage by the news media. Occasionally, however, an event will trigger a media storm, with voluminous and widespread coverage lasting for weeks instead of days. In this work, we develop and apply a pairwise article similarity model, allowing us to identify story clusters in corpora covering local and national online news, and thereby create a comprehensive corpus of media storms over a nearly two year period. Using this corpus, we investigate media storms at a new level of granularity, allowing us to validate claims about storm evolution and topical distribution, and provide empirical support for previously hypothesized patterns of influence of storms on media coverage and intermedia agenda setting.