Honglin (虹霖) Bao
Innovation, AI, and Computational Social Science
Doctoral student in data science, University of Chicago
Contact: honglinbao at uchicago dot edu
"Science must begin with myths, and with the criticism of myths." - Karl Popper
Hi there! I am Honglin (he/him). I am a computational social scientist and data science doctoral student in the UChicago Knowledge Lab working with James A. Evans.
I study the drivers of innovation -- how new ideas are born and spread; how social, scientific, and technological institutions accelerate discovery and influence collective cognition, collaboration, and evaluation; and how innovation and broader societal issues like inequality and policy interact.
I use and develop computational methods: network analysis, NLP, machine learning, causal inference/econometrics, agent-based modeling, and AI for simulating and automating innovation.
Broadly, I am interested in the general theory behind novelties in human understanding and LLMs, how machines complement human imagination, and how Generative AI augments social science methodologies and paradigms.
My works appear in top peer-reviewed journals and proceedings across computer science, network science, and social sciences including Nature Communications.
I have backgrounds in mathematics, computer science, social science, and evolutionary biology. Before Chicago I graduated from Michigan State and was a research associate at Harvard Business School (Organizations and Management). I am from Northeast China (东北) where I volunteered for LGBTQ health for years. In my free time you can find me in the weight room, swimming pool, or running outside.
I widely collaborate with innovation scholars outside Chicago. Drop me an email if you are interested in working together!
Selected Papers
I advertise the papers I think a lot about through my X highlights.
AI & Scientific Innovation
Where there's a will there's a way: ChatGPT is used more for science in countries where it is prohibited [Preprint]
Honglin Bao=, Mengyi Sun=, Misha Teplitskiy
TL; DR: Restricting ChatGPT geographically is ineffective in science, yet ChatGPT's impact on improving research quality remains limited.
Presented at Harvard D^3 Institute research workshop 2024.
Innovation Diffusion
Cultural Ties in American Sociology [Preprint]
Revise & Resubmit, Poetics ("field top" in cultural sociology)
Alex Xiaoqin Yan, Honglin Bao, Tom R. Leppard, Andrew P. Davis
TL; DR: Status and geo-location shape "cultural ties" and the formation of schools of thought in American sociology.
Presented at ASA (Meeting of the American Sociological Association) Science Knowledge and Technology Section 2023, Harvard D^3 Institute research workshop 2023, and NC State Structures, Identities, and Society Seminar 2023. Slides
Evaluation of Innovation
A simulation-based analysis of the impact of rhetorical citations in science [Paper]
Nature Communications, 2024
Honglin Bao, Misha Teplitskiy
TL; DR: Using a counterfactual simulation, we find "bad" citing without intellectual influence reduces the reproduction of inequality in science.
Featured in Nature's Computational Social Science Collection; Selected media coverage “Swarm Agents Club 集智俱乐部”; X thread
Presented at Computational Organization Modeling Society Brown Bag Seminar 2023 and Harvard D^3 Institute research workshop 2022. Slides
Selected Work in Progress
Honglin Bao, Kai Li. Momentum makers: New conferences and scientific transformation.
Presented at ASIS&T MET-STI 2024 (Workshop on Informetric, Scientometric, and Scientific and Technical Information Research).
Alex Xiaoqin Yan=, Honglin Bao=, Tom R. Leppard, Andrew P. Davis. "Vogue" in American Sociology.
Oral presentations at ICSSI (Intl. Conf. on Science of Science and Innovation) 2024 and IC2S2 (Intl. Conf. for Computational Social Science) 2024.
Credibility in Science, with Haohan Shi, Mengyi Sun, and Misha Teplitskiy.
Attention in Science, with James Evans.
Services
Occasional reviewer for IC2S2 (Intl. Conf. for Computational Social Science), International Journal of System Science, Theoretical Computer Science - Natural Computing.