George Chacko

For more information

• The ERNIE Project

Research Statement

My scientific interests oscillate around novelty in science, impact, peer review, knowledge diffusion, and research communities. A related interest is the social interactions that drive scientific recognition and achievement. Analyzing citations to the scientific literature, at scale, is central to my work and emphasis is placed on any results being of value to at least one of four stakeholders: (i) research funders, who want to know what their support has achieved and what it might in future, (ii) research institutions who ask the same questions as funders but are recipients of funds and must strategize to sustain their existing support and/or augment it, (iii) providers of research analytical services who think beyond the confines of commonplace global metrics such as the h-index and its well documented limitations, and (iv) finally, the evaluation community itself.

More recently, I have drifted towards the identification and characterization of research communities that form around scientific questions. I am establishing new collaborations within and outside the department to support this work. The techniques used in my studies build upon work in scientometrics, sociology, science history, and computer science. A preprint of our latest work on community finding is posted on ArXiv https://arxiv.org/abs/2111.07410 and has since been accepted: https://doi.org/10.1162/qss_a_00184.

Of possible interest is a course on scientometrics that is being taught in the fall semester of calendar year 2022: https://csscientometrics.web.illinois.edu/2022/04/14/cs-598-computational-scientometrics-fall-2022/

Selected Articles in Journals

• Wedell, E., Park, M., Korobskiy, D., Warnow, T., and Chacko, G. Center-Periphery Structure in Research Communities (2022) Quantitative Science Studies (preprint also on ArXiv)
• Chandrasekharan, S., Zaka, M., Gallo, S., Zhao, W., Korobskiy, D., Warnow, T., & Chacko, G. Finding Scientific Communities in Citation Graphs : Articles and Authors. (2021) Quantitative Science Studies. doi:10.1162/qss_a_00095
• Bradley, J., Devarakonda, S., Davey, A., Korobskiy, D., Liu, S., Lakhdar-Hamina, D., Warnow, T., & Chacko, G. (2020). Co-citations in context: Disciplinary heterogeneity is relevant. Quantitative Science Studies, 1, 1-13. doi:10.1162/qss a 00007
• Bornmann, L., Devarakonda, S., Tekles, A., & Chacko, G. (2020). Disruptive papers published in Scientometrics: meaningful results by using an improved variant of the disruption index originally proposed by Wu, Wang, and Evans (2019). Scientometrics. doi:10.1007/s11192-020-03406-8.
• Bornmann, L., Devarakonda, S., Tekles, A., & Chacko, G. (2020). Are disruption index indicators convergently valid? The comparison of several indicator variants with assessments by peers. Quantitative Science Studies. doi:10.1162/qss a 00068.
• Devarakonda, S., Bradley, J., Korobskiy, D., Warnow, T., & Chacko, G. (2020). Frequently co-cited publications: Features and kinetics. Quantitative Science Studies. doi: 10.1162/qss a 00075.
• Devarakonda, S., Korobskiy, D., Warnow, T., & Chacko, G. (2020). Viewing Computer Science through Citation Analysis Salton and Bergmark Redux. Scientometrics. doi:10.1007/s11192-020-03624-0.
• Zhao, W., Korobskiy, D., Chandrasekharan, S., Merz, K., & Chacko, G. (2020). Converging interests- chemoinformatics, history, and bibliometrics. Journal of Chemical Information and Modeling. doi:10.1021/acs.jcim.0c01098
• Zhao, W., Korobskiy, D., & Chacko, G. Delayed Recognition; A Co-citation Perspective (2020) Frontiers in Research Metrics and Analytics doi:10.3389/frma.2020.577131
• Keserci, S., Livingston, E., Wan, L., Pico, A.R., and Chacko, G. (2017) Heliyon doi: 10.1016/j.heliyon.2017.e00442
• Boyack, K.W., Chen, M-C, & Chacko, G. (2014) Characterization of the Peer Review Network at the Center for Scientific Review, National Institutes of Health. PLOS One doi: 10.1371/journal.pone.0104244

Invited Lectures

• Detecting Research Communities From The Scientific Literature

Recent Courses Taught

• CS 598 GGC - Computational Scientometrics