Scientometrics special issue 'AI for Scientometrics'
lin zhang
Dear ISSI members, colleagues, and friends,
We are delighted to announce the formal launch of our Scientometrics special issue Artificial Intelligence for Scientometrics. This special issue invites the scientometrics community to explore the great potential and challenges of integrating AI, particularly large language models, into broad scientometric research.
Please find our call for papers below. We look forward to receiving your high-quality submissions.
Many thanks and all best,
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Call for Papers
Scientometrics Dedicated Issue on
Artificial Intelligence for Scientometrics
Background
Artificial intelligence (AI) has begun to transform human society by extending beyond its original domain of computer science and becoming a significant enabler of broad scientific research and real-world applications. With its human-like capabilities such as perceiving, learning, reasoning, and performing, AI for Science (AI4Science) has been a comprehensive initiative across the scientific communities. The scientometrics community, with its long-standing engagement in data science, has observed a rapid increase of AI application in recent studies, among others, using Bayesian networks (e.g., latent Dirichlet allocation) for identifying research topics, utilising pre-trained language models (e.g., BERT) to represent knowledge entities, and developing machine learning-based prediction models to foresee citation impact and knowledge trajectories.
The increasing success of large language models (LLMs) signals that AI is reaching a tipping point, heralding a new revolution from extrinsic working patterns to intrinsic thinking paradigms. This shift urges the scientometrics community to investigate the potentials and challenges in this AI-driven revolution. We particularly highlight the following challenges:
- Design: How can we create a comprehensive research framework of AI4Science, incorporating AI techniques for designing scientometric research?
- Communication: How can we responsibly integrate LLMs with human knowledge for conducting scientometric studies (e.g., LLM-aided academic writing and publishing in the context of scientometrics, and LLM-supported metrics research and evaluative research)?
- Tools: How can we develop effective and explainable AI tools for broad scientometric studies (e.g., deep literature analysis using LLMs, and LLMs as part of new scientometric tools)?
This special issue calls on the scientometrics community to publish high-quality research on broad topics of AI for scientometrics, including fundamental theories, conceptual understandings, novel methodological developments, and practical applications that address urgent scientometric needs.
Topics
Topics include but are not limited to:
- AI for evaluative research (including peer review/expert opinion and their evaluation, etc.)
- AI for metrics research (including LLM-enhanced cognitive link analysis, citation context analysis, sentiment analysis, etc.)
- AI for literature-based analysis (including entity extraction, knowledge graphs, full-text content analysis, etc.)
- AI for scientific information retrieval and access (including academic GPTs, retrieval-augmented generation, etc.)
- AI for patentometrics, technometrics, and altmetrics
- AI-empowered prediction models for scientometrics, e.g., predicting research trends, impact, quality, etc., and technological forecasting
- LLMs for research communication, e.g., publishing, scientific writing, qualitative approaches (e.g., academic surveys), and data reporting and visualisation
- LLMs or AI4Science as part of new scientometric tools
- AI4Science for designing and conducting research in the context of scientometrics
- AI ethics in scientometrics, e.g., biases, transparency, and the impact of AI-generated content on scientometric research.
Submission Types
We will invite notable and active researchers in this topic to contribute Invited papers. We also call for papers relevant to the scientometrics community as Contributed papers. All submissions will undergo the journal’s standard reviewing procedure.
In particular, we welcome submissions about research articles, reviews, and discussion & opinion papers.
Estimated Submission Timelines
- Submission system opens: September 1, 2024
- Submission system closes: February 28, 2025
- Publication of the special issue: September 1, 2025
Note:
- Once the system is open, all submissions will be processed individually, without waiting for the system to close.
- Accepted manuscripts will be available online upon acceptance individually. The print version will be published as a physical dedicated issue along with the Editorial note introducing this special issue.
- The submission channel can be accessed through the EM website of Scientometrics (under the SI of ‘AI4SCIM’: https://www.editorialmanager.com/scim/default.aspx.)
Guest Editors
Yi Zhang
Australian Artificial Intelligence Institute, Faculty of Engineering and Information Technology, University of Technology Sydney, Australia
Chengzhi Zhang
Department of Information Management, Nanjing University of Science and Technology, China
Kayvan Kousha
Faculty of Arts, Business, and Social Sciences, University of Wolverhampton, United Kingdoms
Birger Larsen
Department of Communication and Psychology, Aalborg University, Denmark