paper-with-me

Papers

Beyond Citations: Measuring Idea-level Knowledge Diffusion from Research to Journalism and Policy-making

2025-11-05 · Yangliu Fan, Kilian Buehling, Volker Stocker arxiv

Despite the importance of social science knowledge for various stakeholders, measuring its diffusion into different domains remains a challenge. This study uses a novel text-based approach to measure the idea-level diffusion of social science knowledge from the research domain to the journalism and policy-making domains. By doing so, we expand the detection of knowledge diffusion beyond the measurements of direct references. Our study focuses on media effects theories as key research ideas in the field of communication science. Using 72,703 documents (2000-2019) from three domains (i.e., research, journalism, and policy-making) that mention these ideas, we count the mentions of these ideas in each domain, estimate their domain-specific contexts, and track and compare differences across domains and over time. Overall, we find that diffusion patterns and dynamics vary considerably between ideas, with some ideas diffusing between other domains, while others do not. Based on the embedding regression approach, we compare contextualized meanings across domains and find that the distances between research and policy are typically larger than between research and journalism. We also find that ideas largely shift roles across domains - from being the theories themselves in research to sense-making in news to applied, administrative use in policy. Over time, we observe semantic convergence mainly for ideas that are practically oriented. Our results characterize the cross-domain diffusion patterns and dynamics of social science knowledge at the idea level, and we discuss the implications for measuring knowledge diffusion beyond citations.

📄 PDF Abstract BibTeX arXiv:2511.03378

Code (0)

등록된 구현이 없습니다.

Similar Papers 제목 키워드 기반

Beyond Citations: Measuring Novel Scientific Ideas and their Impact in Publication Text

2023-09-28 · Sam Arts, Nicola Melluso, Reinhilde Veugelers

New scientific ideas drive progress, yet measuring scientific novelty remains challenging. We use natural language processing to detect the origin and impact of new ideas in scientific publications. To validate our metho…

Novelty Detection

Hierarchical Memorization in Large Language Models: Evidence from Citation Generation

2025-11-12 · Junichiro Niimi arxiv

Large language models (LLMs) generate fluent text across a wide range of tasks, but the fabrication of non-existent academic citations remains a critical and well-documented failure mode. Building on prior work that fram…

Why Neighborhoods Matter: Traversal Context and Provenance in Agentic GraphRAG

2026-05-14 · Riccardo Terrenzi, Maximilian von Zastrow, Serkan Ayvaz arxiv

Retrieval-Augmented Generation can improve factuality by grounding answers in external evidence, but Agentic GraphRAG complicates what it means for citations to be faithful. In these systems, an agent explores a knowledg…

HLM-Cite: Hybrid Language Model Workflow for Text-based Scientific Citation Prediction

2024-10-10 · Qianyue Hao, Jingyang Fan, Fengli Xu, Jian Yuan 외

Citation networks are critical in modern science, and predicting which previous papers (candidates) will a new paper (query) cite is a critical problem. However, the roles of a paper's citations vary significantly, rangi…

Binary ClassificationCitation PredictionLanguage ModelingLanguage Modelling+1

The Noisy Path from Source to Citation: Measuring How Scholars Engage with Past Research

2025-02-27 · Hong Chen, Misha Teplitskiy, David Jurgens

Academic citations are widely used for evaluating research and tracing knowledge flows. Such uses typically rely on raw citation counts and neglect variability in citation types. In particular, citations can vary in thei…

Sentence