People
Ly Dinh
Assistant Professor
CONTACT
Office: CIS 2022
Email
BIO
Dr. Ly Dinh is a computational social science researcher studying how research methods such as network analysis, social simulation models, and text analysis, can be used to advance our understanding of various social and organizational systems. Dr. Dinh's current projects place network science at the core to understand and explain a number of social and organizational phenomena ranging from egocentric networks to interagency emergency response networks. She also develops and tests new measures to capture the complexities of social interactions that can be observed at multiple levels of the network (ego, dyad, triad, subgroup, whole network). Dr. Dinh's research has appeared in Scientific Reports, Computational Communication Research, and peer-reviewed outlets in computational social science and crisis informatics. Dr. Dinh is a recipient of the 2020 Grace Hopper Scholar for Women in Computing, and a 2018 Network Science Fellow at Visible Networks Labs.
EDUCATION
- Ph.D., University of Illinois at Urbana-Champaign
- M.A., University of Illinois at Urbana-Champaign
- B.A., University of Southern California
Recent Publications & Research
- Dinh, L., Barely, W., Johnson L., Allan, B. (2024) Hyperauthored papers disproportionately amplify important egocentric network metrics. https://direct.mit.edu/qss/article/doi/10.1162/qss_a_00307/120830/Hyperauthored-papers-disproportionately-amplify.
- Dinh, L., Sarol, J., Jeoung, S., & Diesner, J. (2023). Are we projecting gender biases to ungendered things? Differences in referring to female versus male named hurricanes in 33 years of news coverage. Computational Communication Research. https://doi.org/10.5117/CCR2023.1.006.DINH.
- Dinh, L.*, Rezapour, R.*, Jiang, L., & Diesner, J. (2022). Enhancing structural balance to analyze signed digraphs of real-world organizational networks. Front. Hum. Dyn. 4:1028393. https://doi.org/10.3389/fhumd.2022.1028393.
- Aref, S.*, Dinh, L.*, Rezapour, R*, & Diesner, J (*Equal Contribution). Multilevel structual evaluation of signed directed social networks based on balance theory. Scientific Reports 10, 15228 (2020). https://doi.org/10.1038/s41598-020-71838-6.
- Dinh, L., Kulkarni, S., Yang, P., & Diesner, J. (2022). Reliability of Methods for Extracting Collaboration Networks from Crisis-related Situational Reports and Tweets. Proceedings of the ISCRAM Asia Pacific, 2022. Melbourne, Australia.
- Dinh, L., & Parulian, N. (2020). COVID-19 Pandemic and Information Diffusion Analysis on Twitter. Proceedings of the Association for Information Science and Technology, 57(1), e252. https://doi.org/10.1002/pra2.252. Pittsburg, PA.