10.7910/DVN/ZA6YEN Shen-Bayh, Fiona Fiona Shen-Bayh https://orcid.org/0000-0001-5243-2110 University of Maryland Kitagawa, Risa Risa Kitagawa https://orcid.org/0000-0002-9885-8173 Northwestern University Harvard Dataverse 2023 Social Sciences international courts media text-as-data Africa The Journal of Politics Dataverse The Journal of Politics Dataverse Shen-Bayh, Fiona Fiona Shen-Bayh University of Maryland 2023-06-22 2023-07-12 2023-07-21 1632 32133 19008885 575595735 11047630 5947 9707 93057821 688979 409009 11056661 text/plain type/x-r-syntax text/tab-separated-values application/gzip application/pdf application/rtf type/x-r-syntax application/gzip application/gzip application/gzip application/pdf 2.0 Creative Commons CC0 1.0 Universal Public Domain Dedication. Recent advances in text-as-data provide new opportunities to document how elites shape public discourse on contentious issues. Using a novel word embeddings approach to measure elite-driven political narratives in local news, we analyze Kenyan newspaper coverage of the International Criminal Court's (ICC) prosecutions against domestic leaders. We train our embeddings on an original corpus of 5,292 Kenyan newspaper articles from 2007-2020 and identify significant changes in how local media vilifies the ICC before, during, and after major investigations. We find that as the case progressed, the ICC became more strongly associated with terms of bias and illegitimacy, an association which quickly dissipated after the Court terminated its last proceeding. Our approach illustrates the utility of text-based measures of political sentiment on contentious issues, with implications for research on media narratives, the effects of controversial jurisprudence on public discourse, and backlash against international institutions.