For More Information
- CS 598: Computational Scientometrics
My scientific interests oscillate around novelty in science, impact, peer review, knowledge diffusion, and research community structure. 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. 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've 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.
Another manuscript on overlapping clusters has been submitted for review.
Of possible interest is a graduate course on scientometrics that is being taught in the fall semester of calendar year 2022.
Also of possible interest may be this link that leads to information on my collaboration with Tandy Warnow, with whom I have written a number of papers. This collaboration is now supported by a grant in 2022 from the Insper:Illinois collaboration as well as a research project from the Oracle Corporation in the form of cloud credits that cover the operational costs of a a VM and cloud storage in the Oracle Cloud Infrastructure. These collaborations involve Charles Kirschbaum and Fabio Ayres from Insper and my long time collaborator Dmitriy Korobskiy at NTT DATA Services (who contributes his effort during his off hours from work because he enjoys working with us).
In the spring semester of 2022, I worked with with undergraduates Hemank Kohli and Franklin Moy both from the ECE program and Akhil Jakatdar from the computer science program. In the summer of 2022, Elaina Wittmer and Sid Ahuja from the iCAN program at Illinois took a CS597 course with me. Akhil's work resulted in a manuscript being submitted in August.
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
- AOC; Assembling Overlapping Clusters (2022) Jakatdar, A; Warnow, T; and Chacko, G. Submitted to Quantitative Science Studies. https://arxiv.org/abs/2208.04842 [on August 18 2022, we discovered a coding error that impacts modularity calculations. We are evaluating the effect of this error. A revision will be available as soon as results are regenerated.]
Recent Courses Taught
- CS 598 GGC - Computational Scientometrics