The rapid advancements in Artificial Intelligence (AI), particularly the emergence of large language models (LLMs) such as ChatGPT and DeepSeek, have brought transformative changes to the entire scientific research ecosystem. As evidenced by the science map of more than 10,000 papers mentioning ChatGPT (see Figure 1), nearly every field of research is actively engaging with and discussing the implications of these technologies.

The science of science—encompassing scientometrics, informetrics, and bibliometrics—is one of the fields profoundly impacted by LLMs, yet it has also been quick to embrace their potential. Cutting-edge research is exploring the use of LLMs for tasks such as research evaluation (Thelwall, 2024), modeling scientific communities with AI agents (Piao et al., 2025), and even aiding in idea generation and paper writing (Si et al., 2024). However, alongside these opportunities, we must also address the challenges posed by AI-generated content (AIGC), which has emerged as a significant concern in academic integrity and misconduct (Li & Shen, 2024).

As a journal dedicated to bridging data-driven science of science research and the broader research ecosystem (Yang et al., 2025), we are thrilled to announce a special topic focused on the theme “AI for Science of Science.” We invite researchers, practitioners, and thought leaders to contribute original research articles, data papers, opinions, and reviews that explore the following topics (but are not limited to):

$\bullet$ Novel applications of AI in knowledge discovery, bibliometric analysis, and technology forecasting.

$\bullet$ AI for enhancing research evaluation and broadening the impact of scientific research.

$\bullet$ Pros and cons of AI in reshaping the publishing ecosystem (e.g. addressing issues like “publish or perish” and academic misconduct).

$\bullet$ Exploration of AI agents for science of science and innovation economics research.

$\bullet$ Ethical considerations and challenges in AI applications within science of science and other research practices.

$\bullet$ Datasets and frameworks for evaluating AI tools in the context of science of science.

This special topic aims to foster a deeper understanding of how AI is transforming the science of science, while also addressing the ethical, practical, and methodological challenges that arise. We encourage submissions that push the boundaries of current knowledge and offer innovative perspectives on the intersection between AI and scientific research.

We look forward to your contributions and to advancing the dialogue on this critical and timely topic.