SIG-MET Events

1. SIG-MET Distinguished Speaker Series: Opening Lecture by Dr. Cassidy Sugimoto

Speaker: Dr. Cassidy Sugimoto

Dr. Cassidy Sugimoto is Tom and Marie Patton Professor and School Chair in the School of Public Policy at Georgia Institute of Technology. Her research examines the formal and informal ways in which knowledge is produced, disseminated, consumed, and supported, with an emphasis on issues of diversity, equity, and inclusion.

Title: How to Be a Scientific Superpower

This talk explores the systemic factors and policy frameworks that enable nations and institutions to achieve scientific excellence and global influence in research. Drawing on her metascience research, Sugimoto explores how indicators around investments and production have been the primary drivers of what constitutes a "superpower". Weaving together historical evidence, she argues for indicators that consider diffusion and epistemic influence and demonstrates the current polycentric organization of global science. The conclusion will focus on how scientists, policymakers, and administrators can be more intentional in setting the global scientific agenda.

Lecture Guide:

Registration - https://www2.asist.org/events/Details/sig-met-invited-talk-1-1565651?sourceTypeId=Hub

Location - Online event, the lecture link will be sent to registered attendees via email.

Time - 9:00-10:00 am USA time on Friday, December 5th, 2025.

Sponsors:

 

2. SIG-MET Distinguished Speaker Series: Lecture by Dr. Yong-Yeol (YY) Ahn

Speaker: Dr. Yong-Yeol (YY) Ahn

Dr. Yong-Yeol (YY) Ahn is a network and data scientist whose work combines network science, machine learning, and the study of complex social, biological, and information systems. He is a Quantitative Foundation Distinguished Professor at the University of Virginia’s School of Data Science. Before joining UVA, he was a Professor at Indiana University’s CNetS, Luddy School of Informatics, Computing, and Engineering and a Visiting Professor at MIT. Earlier, he worked as a postdoctoral research associate at the Center for Complex Network Research at Northeastern University and as a visiting researcher at the Center for Cancer Systems Biology at Dana-Farber Cancer Institute after completing his PhD in Statistical Physics from KAIST. His research focuses on the architectures of complex systems—how networks shape behavior, cognition, and scientific progress—and on developing methods in network analysis, machine learning, and natural language processing to investigate these mechanisms at scale. He is the co-author of Working with Network Data. His work has been recognized with several honors, including the Microsoft Research Faculty Fellowship.

Title: The Geometry of Science

What would scientometrics look like if scientific ideas lived in a concrete physical space? Deep representation learning now allows us to imagine such a shared knowledge embedding space where scholarly works, ideas, and other entities can coexist. Yet these powerful models are often black boxes, hard to translate into interpretable metrics. In this talk, I show that a fundamental understanding of embedding methods can make this space interpretable, allowing its geometry to be measured directly. The flow of scientists between institutions follows a gravity law governed by distance in the space, and scientific disruption can be captured through the geometric displacement of a field's trajectory — without relying on sparse local citation links. This embedding-based framework may offer a unified language for describing how science attracts, disrupts, and moves, complementing traditional citation-based indicators.

Lecture Guide:

• Registration - https://www2.asist.org/ap/Events/Register/xRFXn32sMCYC7
• Location - Online event, the lecture link will be sent to registered attendees via email.
• Time - 9:00-10:00 AM (EDT) USA time on Tuesday, March 17th, 2026.

Organizers:

• ASIS&T SIG-MET
• Faculty of Education, The University of Hong Kong
• School of Information Management, Sun Yat-sun University

 

3. Call for Papers

[METSTI 2026]: ASIS&T METSTI Annual Symposium on Informetric, Scientometric, Scientific and Technical Information Research
To be held in conjunction with the ASIS&T Annual Meeting [Bangkok, Thailand, 6-10, November, 2026]

 

Overview

The ASIS&T Special Interest Group for Metrics (SIG-MET) and Special Interest Group on Scientific and Technical Information (SIG-STI) invite submissions for the combined METSTI 2026 Symposium on Informetric, Scientometric, Scientific and Technical Information Research, to be held as part of the ASIS&T Annual Meeting 2026.

This Symposium will provide a forum for researchers, practitioners, and students to present and discuss current research and emerging issues in metrics relevant fields including altmetrics, bibliometrics, scientometrics, webometrics, informetrics, and related issues about advancement of theories, methodologies, tools of scientific and technical information (STI) management and utilization.

The Symposium aims to foster interaction among participants at all career stages, encourage feedback on ongoing work, and build collaborations across institutions and regions.

Theme

The theme of this satellite meeting is Metrics and Sci-tech information in a Connected World. Building on the ASIS&T 2026 conference theme, this symposium examines how metrics can help us understand and foster connections across regions, languages, and disciplines.

Metrics provide valuable tools for examining crossboundary connections—such as how scientific teams form, how ideas from different fields combine, and how policies succeed in breaking down barriers. However, metrics also present challenges. The data underlying many metrics suffers from limited and biased coverage, and analytical techniques may obscure important connections when they do occur. Furthermore, the very act of measuring can shape what we're trying to understand: metrics can either reinforce existing boundaries or create incentives for crossing them.

This symposium welcomes applied, methodological, and theoretical contributions that explore how metrics can advance our understanding of cross-boundary connections or examine how measurement practices themselves influence collaboration, knowledge sharing, and equity across diverse communities and contexts.

Topics of Interest

We welcome submissions on (but not limited to) the following topics:

• Altmetrics (including social media metrics)
• Citation, co-citation, bibliographic coupling, and co-authorship analysis
• Indicators and metrics for research evaluation (individual, institutional, national, global)
• Open science, open data, and their measurement
• Mapping of science and knowledge domains
• Patent and innovation indicators
• Bibliometricenhanced information retrieval and recommender systems
• Network analysis of scholarly communication and collaboration
• Responsible metrics, research assessment reforms, and policy implications
• Methodological advances (data sources, normalization, field delineation, classification, visualization)
• Tool development, platforms, and infrastructures for metric analyses
• Domain-specific or regional studies in scientometrics/ informetrics
• AI for science/scientometrics
• Research integrity
• Scholarly Communication
• Science, technology & innovation policy
• Social dimensions of metrics and their use
• Scientific and technical information for science
• Information for technical innovation
• Scientific and technical information for decision
• Information for interdisciplinary collaboration
• Scientific and technical information enable enterprise growth
• Scientific and technical information for industry innovation
• Scientific and technical information for regional growth
• Scientific and technical information management
• Scientific and technical information community
• Ethics of scientific and technical information
• Scientific and technical information users, behaviours
• AI for scientific and technical information mining, analysis
• Causal, cognitive reasoning of scientific and technical information
• Knowledge augmented generation of STI field
• Multimodal learning of scientific and technical information
• Intellectual property issues of scientific and technical information
• Scientific and technical information sharing and platform

Submissions presenting work in progress, early-stage ideas, or novel methodological approaches are especially encouraged.

Submission Types

We invite the following types of contributions:

1. Research Papers

• Completed or nearly completed research, including objectives, methods, data, results, and implications.

2. Work-in-Progress Papers

• Ongoing projects, preliminary results, or methodological ideas seeking feedback.
• Conceptual or theoretical contributions, critiques, visions for the field, or reflections on responsible and ethical uses of metrics.
• Short description of tools, platforms, datasets, or services related to scientometrics/ informetrics, including use cases and screenshots

Formatting

• Use ASIS&T long/short paper template. Templates are available at https://www.asist.org/am26/am26-submission-types/
• Submissions should be Word, in English.

Submission System

• Please email submissions to sigmet.asist@gmail.com
• Track name: "METSTI Annual Symposium 2026"

Important Dates

• Submission deadline: [June 25th, 2026]
• Notification of acceptance: [July 25th, 2026]
• Camera-ready due: [August 1st, 2026]
• Symposium date: [November 6th, 2026, – during the Annual Meeting]

Late submissions and deadline extensions, if any, will be announced via the SIG-MET mailing lists, ASIS&T channels, and social media.

Review and Publication

All submissions will undergo peer review by the symposium academic and program committee, based on:

• Relevance to the symposium and SIG-MET
• Novelty and significance
• Methodological rigor
• Clarity of presentation
• Potential to foster discussion and future research

Accepted contributions will be:

• Presented at the symposium as talks, lightning talks, or demos (format assigned based on content and number of submissions).
• Included in ASIS&T SIGMET webpage/Zenodo if permitted by the authors.

Mode

• In-person
• Registration is handled via ASIS&T Annual Meeting registration. Additional symposium registration details will be available on the ASIS&T website.

Awards

• Top 25% submissions nominated for best paper awards, with certificate
• Top 3 best paper awards, $300, with certificate.

Organizers

Symposium Chair

• Jingzhu Wei, Sun Yat-sen University, China
• Houqiang Yu, Sun Yat-sen University, China

Academic Chair

• Dakota Murray, University of Albany, USA
• Haihua Chen, University of North Texas, USA
• Chenwei Zhang, Hong Kong University, China
• Lesego Makhafola, University of Pretoria, South Africa
• Priya Vaidya, Lovely Professional University, India

Program Chair

• Zhichao Fang, Renmin University of China, China
• Likun Cao, Purdue University, USA
• Jianhua Hou, Sun Yat-sen University, China

On behalf of ASIS&T SIG-MET and SIG-STI.

Contact

For questions about submissions or the workshop, please contact:

[Zhichao Fang]: [fangz@ruc.edu.cn]

Subject line: “METSTI Symposium 2026”

 

4. SIG-MET Distinguished Speaker Series: Lecture by Dr. Mike Thelwall

Speaker: Dr. Mike Thelwall

Mike Thelwall is a Professor of Data Science in the School of Information, Journalism and Communication at the University of Sheffield in the UK, and a visiting professor at Peking University, University of Malaya, and Wolverhampton University. He investigates quantitative methods to support research evaluation, with a current focus on large language models for research quality evaluation, and a previous emphasis on alternative indicators for research impact. He leads the AI Peer project investigating whether and how ChatGPT and similar models can support research assessment as well as the LLMs Supporting Grant Peer Review project. His recent free book is: Quantitative Methods in Research Evaluation: Citation Indicators, Altmetrics, and Artificial Intelligence (https://doi.org/10.48550/arXiv.2407.00135). He sits on eight editorial boards, including Journal of Data and Information Science and Journal of the Association for Information Science and Technology.

Title: Can Large Language Models replace citation data for some types of bibliometric analysis?

Recent evidence has shown that some Large Language Models (LLMs) can score published journal articles for research quality in most fields in a way that associates more strongly than field normalized citation counts with expert judgements. This suggests that LLMs may be more useful than citation data for some contexts in which citation data is currently used. Also, since LLM scores are available earlier than mature citation counts, they may be useful for some applications where citations are unavailable. Nevertheless, the reason why LLMs have this capability is not clear, their biases have not been extensively explored, and there may be unwanted systemic effects from using LLMs in formative evaluations. This talk will discuss these issues and make some recommendations for future research.

Lecture Guide:

• Registration - https://www2.asist.org/ap/Events/Register/yEFOjZ8ceCoCR
• Location - Online event, the lecture link will be sent to registered attendees via email.
• Time - 8:00-9:00 AM (EDT) USA time on Tuesday, June 26th, 2026.

Organizers:

• ASIS&T SIG-MET
• School of Information Resource Management, Renmin University of China
• School of Information Management, Sun Yat-sun University

 

5. SIG-MET Distinguished Speaker Series: Lecture by Professor Johann Mouton

Speaker: Prof. Johann Mouton

Professor Johann Mouton is Director of the DSTI-NRF Centre of Excellence in Scientometrics and STI Policy and Professor at CREST, Stellenbosch University. A leading expert in scientometrics, research evaluation and science policy, he has published extensively, supervised more than 100 postgraduate students, and contributed significantly to doctoral education and research capacity development in Africa. He founded the African Doctoral Academy in 2009 and was recognised in ASSAf's Legends of South African Science in 2020. His current research focuses on predatory publishing, science funding in Africa, doctoral graduate mobility, and knowledge production in South African universities.

Title: An Overview of the Scientometric Work at CREST and the DSTI-NRF Centre of Excellence in Scientometrics and STI Policy

The talk will provide examples of scientometric and bibliometric studies undertaken by CREST. It will also include demonstrations of two digital platforms that we have recently developed: the first is a dashboard on STI Funding flows to Africa; the second, a dashboard on the state of 13 basic scientific fields in South Africa.

Lecture Guide:

• Registration - https://www2.asist.org/events/Details/sig-met-distinguished-speaker-series-lecture-by-professor-johann-mouton-1930276?sourceTypeId=Hub
• Location - Online event, the lecture link will be sent to registered attendees via email.
• Time - 3:00-4:00 AM (EDT time), 9:00-10:00 AM (CET time) on Tuesday, September 22nd, 2026.

Organizers:

• ASIS&T SIG-MET
• University of Pretoria
• School of Information Management, Sun Yat-sun University

 

6. SIG-MET Distinguished Speaker Series: Lecture by Professor Giovanni Abramo

Speaker: Prof. Giovanni Abramo

Giovanni Abramo holds a Laurea in electrical engineering from the University of Rome "Sapienza" and a Master of Science in Management from the Massachusetts Institute of Technology (MIT). In November 2023, after nearly 40 years at the National Research Council of Italy (CNR) as a Research Director, Giovanni transitioned to Universitas Mercatorum in Italy, where he is now a Full Professor of Management of Innovation and Entrepreneurship. In 2004, Giovanni founded the CNR Laboratory for Studies in Research Evaluation. In 2006, he established Research Value, a CNR spinoff company dedicated to providing research evaluation services to research institutions and governments. Since 2017, he has also held the title of Honorary Professor of Management at the University of Waikato in New Zealand. Throughout his career, Giovanni has consulted for prestigious organizations, including the United Nations, the European Commission, Italian Ministries, and various public and private entities. His research focuses on how individuals, organizations, and countries produce and disseminate knowledge, with a special emphasis on research performance evaluation, gender equity, and cross-sector knowledge transfer. Since 2007, he has published over 170 indexed publications in the field of scientometrics in journals such as Quantitative Science Studies, Scientometrics, Journal of Informetrics, JASIST, Higher Education, Research Evaluation, Research Policy, Science and Public Policy, Journal of Technology Transfer, Technovation, R&D Management, and PLoS ONE. In 2023, Giovanni was elected President and Chairman of the Board of the International Society for Scientometrics and Informetrics (ISSI). Giovanni embraces a Zen Buddhist vision of life, “making little distinction between his work and his play, his labor and his leisure, his mind and his body, his education and his recreation, his love and his religion. He hardly knows which is which. He simply pursues his vision of excellence in whatever he does, leaving others to decide whether he is working or playing. To him, he is always doing both”.

Title: Research Performance Evaluation: What to Measure, How to Measure It, and What to Avoid

Research performance evaluation increasingly shapes funding allocation, institutional strategy, academic incentives, and science policy. Yet many widely adopted assessment methods and indicators rest on questionable assumptions and can produce substantial distortions in scores and rankings. This talk examines what should be measured in research evaluation, how it can be measured, and which common practices should be avoided. It begins by clarifying the entities and objectives of research assessment and by comparing peer review with bibliometric approaches. Although peer review remains indispensable where bibliographic databases provide inadequate coverage, its subjectivity, cost, limited scalability, and reliance on small subsets of research outputs raise serious concerns when it is used in large-scale national assessment exercises. Bibliometric evaluation also has important limitations, but, under appropriate conditions, it can offer a more comprehensive, timely, and cost-effective basis for assessing scholarly impact. The presentation then introduces Fractional Scientific Strength (FSS), an indicator designed to measure research productivity as scholarly impact generated per unit of research input. It explains why researchers must be classified by field and why performance at the aggregate level, whether for disciplines, departments, institutions, or countries, should be derived from measurements conducted at the individual level. Finally, the talk critically examines several widely used indicators and assessment systems, including the MNCS, PP(10%), the h-index, international university rankings, and national peer-review exercises. Empirical examples illustrate how unsuitable indicators and methods can significantly alter rankings and lead to misleading conclusions. The central message is straightforward: sound research evaluation requires valid measures, suitable data, and methods aligned with the purpose and context of the assessment. We should count only what counts, while remaining fully aware of what cannot be counted.

Lecture Guide:

• Registration - https://www2.asist.org/events/Details/sig-met-distinguished-speaker-series-research-performance-evaluation-what-to-measure-how-to-measure-it-and-what-to-avoid-1927507?sourceTypeId=Hub
• Location - Online event, the lecture link will be sent to registered attendees via email.
• Time - 9:00-10:00 AM (EDT time), 15:00-16:00 AM (CET time) on Thursday, October 8th, 2026.

Organizers:

• ASIS&T SIG-MET
• School of Information Management, Sun Yat-sun University