mlsanityData to 7 Oct 2026

Promotional Language and the Adoption of Innovative Ideas in Science

arXiv 2406.02798 ↗First posted 4 Jun 2024cs.DL cs.CL cs.CYcited by 8

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Abstract (arXiv)

How are the merits of innovative ideas communicated in science? Here we conduct semantic analyses of grant application success with a focus on scientific promotional language, which has been growing in frequency in many contexts and purportedly may convey an innovative idea's originality and significance. Our analysis attempts to surmount limitations of prior studies by examining the full text of tens of thousands of both funded and unfunded grants from three leading public and private funding agencies: the NIH, the NSF, and the Novo Nordisk Foundation, one of the world's largest private science foundations. We find a robust association between promotional language and the support and adoption of innovative ideas by funders and other scientists. First, the percentage of promotional language in a grant proposal is associated with up to a doubling of the grant's probability of being funded. Second, a grant's promotional language reflects its intrinsic level of innovativeness. Third, the percentage of promotional language predicts the expected citation and productivity impact of publications that are supported by funded grants. Lastly, a computer-assisted experiment that manipulates the promotional language in our data demonstrates how promotional language can communicate the merit of ideas through cognitive activation. With the incidence of promotional language in science steeply rising, and the pivotal role of grants in converting promising and aspirational ideas into solutions, our analysis provides empirical evidence that promotional language is associated with effectively communicating the merits of innovative scientific ideas.

Key facts. Cited by 8 papers in the map (data through 7 Oct 2026). Builds on 15 of its 72 references that are in the map. First posted on arXiv 4 Jun 2024.

Builds on

15 of 72 references.

References · 15

  1. 2019SciBERT: A Pretrained Language Model for Scientific Textcited by 1,404
  2. 2023The science of fake newscited by 94
  3. 2013Tradition and Innovation in Scientists' Research Strategiescited by 26
  4. 2020Neural Embeddings of Scholarly Periodicals Reveal Complex Disciplinary Organizationscited by 16
  5. 2014Invention as a Combinatorial Process: Evidence from U.S. Patentscited by 10
  6. 2019Early-career setback and future career impactcited by 8
  7. 2019Social Influence and Unfollowing Accelerate the Emergence of Echo Chamberscited by 7
  8. 2020Scientific Prizes and the Extraordinary Growth of Scientific Topicscited by 5
  9. 2021Dynamics of Cross-Platform Attention to Retracted Paperscited by 3
  10. 2022The Gender Gap in Scholarly Self-Promotion on Social Mediacited by 3
  11. 2015Mimicry Is Presidential: Linguistic Style Matching in Presidential Debates and Improved Polling Numberscited by 2
  12. 2015Prominent but Less Productive: The Impact of Interdisciplinarity on Scientists' Researchcited by 1
3 more
  1. 2018Citations versus journal impact factor as proxy of quality: Could the latter ever be preferable?cited by 1
  2. 2020Author Mentions in Science News Reveal Widespread Disparities Across Name-inferred Ethnicitiescited by 1
  3. 2021Why ex post peer review encourages high-risk research while ex ante review discourages itcited by 1

Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2025: 2; 2026: 6.

8 papers.