mlsanityData to 14 Oct 2026

War in the Abstract: The Rise and Consequences of Militarized Language in Scientific Communication

arXiv 2606.23462 ↗First posted 22 Jun 2026cs.CL cs.AI cs.CYcited by 0

Not on the map. Why?

Abstract (arXiv)

Scientists do not, by profession, wage war. Yet warfare's vocabulary consistently appears in their abstracts. To quantify the extent to which warfare's vocabulary pervades scientific abstracts, we analyze 21.4 million papers (2010-2025; OpenAlex, PubMed). We additionally run a within-subject war-framing experiment (N = 801; 32,040 trials) designed to provide causal insight into the effects of militaristic language on persuasion. Between 2010 and 2025, the presence of militaristic terms in scientific abstracts rose 48% in OpenAlex and 32% in PubMed, with the rise accelerating sharply after 2019 (cross-database r = 0.96, p < 10-8). The prevalence of militaristic language is conflict-aligned at both country and annual scales (Uppsala Conflict Data Program; r = 0.77-0.84), with the abstracts from the Global South displaying the fastest rise in militaristic language. Among disciplines, social sciences leads in level of such language while engineering and computer science lead in growth. The COVID and post-2022 large-language-model eras also accelerated the rise and narrowed the language gap between native-English-speaking and non-English-speaking countries. In our follow-up experiment, we found that war framing reduced credibility (mean shift -0.176 Likert units, 95% CI [-0.21, -0.14]; dz = -0.28, p < 10-20), funding willingness (dz = -0.12) and policy support (dz = -0.08), with a trend-level increase in sense of urgency (dz = +0.07). Collectively, findings reveal that while scientific abstracts drift toward warfare, the use of militaristic language may erode credibility, funding willingness, and policy support.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 11 of its 65 references that are in the map. First posted on arXiv 22 Jun 2026.

Builds on

11 of 65 references.

References · 11

  1. 2021On the Opportunities and Risks of Foundation Modelscited by 4,033
  2. 2016Diachronic Word Embeddings Reveal Statistical Laws of Semantic Changecited by 221
  3. 2022OpenAlex: A fully-open index of scholarly works, authors, venues, institutions, and conceptscited by 177
  4. 2014Statistically Significant Detection of Linguistic Changecited by 82
  5. 2024Delving into LLM-assisted writing in biomedical publications through excess vocabularycited by 78
  6. 2013Tradition and Innovation in Scientists' Research Strategiescited by 26
  7. 2018Predicting Race and Ethnicity From the Sequence of Characters in a Namecited by 26
  8. 2024Is ChatGPT Transforming Academics' Writing Style?cited by 26
  9. 2020The extent and drivers of gender imbalance in neuroscience reference listscited by 13
  10. 2016Quantitative Evaluation of Gender Bias in Astronomical Publications from Citation Countscited by 10
  11. 2020Framing COVID-19: How we conceptualize and discuss the pandemic on Twittercited by 10

Built on by

Not cited yet.