We study human knowledge as a living interactive network. AI is now fundamentally transforming this network: accelerating knowledge production while narrowing its scope, displacing human contributors, and restructuring the ecosystems through which ideas emerge and spread. These transformations, and what they reveal about both society and AI itself, define our research across four core threads:
Research Areas
We apply data science and network science approaches to explore these key research dimensions:
Collective Knowledge Platforms
We investigate open and crowdsourced knowledge bases—including Wikipedia, Wikidata, GitHub, and Stack Overflow. Our ongoing work explores the systemic impacts of generative AI on these human-contributed ecosystems, specifically examining how LLMs shift developer activity on GitHub and transform technical knowledge sharing on Stack Overflow.
Scientific Knowledge Evolution
We study how scientific breakthroughs and technological innovations emerge and spread in academic papers and patents. Our ongoing research investigates how LLMs are changing citation networks, text usage patterns, and semantic similarity in scientific literature.
Creativity in Cultural Domains
We analyze patterns of human expression and consumption across cultural networks, focusing on art and music. This includes decoding the global spread of streaming content, social links, and trends in fashion and collective preferences.
Ecosystem Pathologies & Scientometrics
We audit and analyze systemic vulnerabilities, biases, and structural barriers within the scientific community. Our work focuses on quantifying the impact of questionable and predatory publishing, tracking citation polarization, and studying demographic disparities in research productivity.
Lab Culture
We are committed to fostering a high-agency, collaborative research environment that puts the researcher first:
Location Independence
We do not enforce physical attendance. Remote research is fully supported, allowing you the flexibility to work from wherever you are most productive.
Research Autonomy
Pursue the research topics you are passionate about. The PI works closely with you to help refine your own questions and ideas into viable scientific projects.
Focus on Science
No mandatory dinners, parties, or administrative distractions. We respect your personal time, focusing solely on productive one-on-one advising and collaborative brainstorming.
Join Us
Anyone who wants to join our lab as a graduate student (M.S. or Ph.D.) is encouraged to contact the PI by email at jinhyuk.yun_at_ssu.ac.kr. Please include your CV and a brief description of your research interests.