Agent-based Modeling in Computational Scientometrics

Note: Agent-based modeling (ABM) should not be confused with agentic AI. 

Overview: To explore the use of agent-based models in studies of real-world or artificial phenomenae and analyze emergent properties observed. A primary interest is the evolving structure of the scientific enterprise but students may, with approval of the instructor, choose to study other problems. The course, will consist of lectures, assignments, class presentations,  and a course project. Course projects may be approached from method-development or discovery perspectives. Students may use existing tools such as Netlogo, Mesa, Repast, and SASCA-ReSA or opt to design, implement, and test entirely new ones.  

Emphasis is placed on interdisciplinary perspectives, the use of open source computing tools, and publicly available data. The course will also feature guest speakers (TBA) who bring unique perspectives and experiences with them. Finally, critical discussion of research literature is coupled to designing and executing a required research project.

Students will be evaluated with respect to their level of engagement in the class, satisfactory completion of homework assignments, and the quality of their presentations, draft, and final project reports. Students are encouraged to publish results from these projects. For those students interested in expanding their course project into a publication, the instructor  will help them develop and improve their work, and finally to submit and publish research findings in journals or conferences.  

Office hours are a combination of in-person and virtual. This course has a single required in-person activity– an in-person presentation of your course project proposal for critical feedback. You will need to schedule this event with the instructor, which will not take place during class lectures but may occur during in-person office hours.

Grading:

• Class participation 10 pts

• Assignments 30 pts

• Class presentations 10 pts

• End of term assignment 50 pts

Prerequisite skills and who should take the course: The course is designed for graduate students in Computer Science, Information Science, and Statistics. However, it is open, with permission of the instructor, to graduate students from other programs as well as to advanced undergraduates. Interested students are urged to contact the instructors before registering.

Minimum Required Skills:  Intermediate to advanced programming skills adequate to design new ABMS or modify existing ones along with fluency in working with large data and interpreting results from analyzing it. 

Introductory material and course reading list: 

• (2025) An Introduction to Agent-based Modeling  (Richard Axtell) [YouTube Lectures]

• ( 1997) A Simulation of the Structure of Academic Research (Nigel Gilbert)

• (2024) A simulation-based analysis of the impact of rhetorical citations in science (Bao and Teplitskiy)

• (2026) Modeling the Global Citation Network using the Scalable Agent-based Simulator for Citation Analysis with Recency-emphasized Sampling (SASCA-ReS) (Park et al. )

Invited Lectures: TBA

Office Hours: TBA