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July 29, 2026Journal of Information Science

The empowerment of Science of Science by large language models: New tools and methods

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Authors

GLGuoqiang LiangJGJingqian GongMLMengxuan Li

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Overview

Comprehensive review on LLMs enhancing scientometric methods and tools, suggesting new research avenues.

Key Points

  • This article reviews the technologies behind large language models and their applications in the Science of Science domain.
  • Comprehensive review of prompt engineering, retrieval-augmented generation, and fine-tuning methods.
  • Historical analysis of the Science of Science development and future applications of LLMs.
  • Discussion on AI agent-based models for scientific evaluation and knowledge graph building.
  • Identified core technologies supporting LLMs, including pre-training and tool learning.
  • Proposed innovative approaches for scientific evaluation through AI and knowledge graphs.
  • Outlined new research fronts that leverage LLM capabilities in the field of scientometrics.

Cite This Study

Liang et al. (2026) studied this question.

synapsesocial.com/papers/6a69a2bcc8da07d9defa687dhttps://doi.org/10.1177/01655515261458219
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