Publications
2026
Jayalath, C., Champon, X., Rand, W., Jasser, J., Garibay, O., Garibay, I.
Data & Policy (Cambridge University Press), 8, e4
Compares targeted, community-based intervention strategies against population-wide responses for shaping information diffusion outcomes on social media.
2026
Champon, X., Staicu, A., Weishampel, A., Jayalath, C., Rand, W.
Journal of the American Statistical Association
Develops categorical-valued functional data analysis methods for latent-process estimation and clustering of social media users' behavioral trajectories.
2026Accepted
Jayalath, C., Rand, W., Garibay, I.
Conference of the Computational Social Science Society of the Americas (CSS), Santa Fe, NM
Introduces a conformal-prediction approach to identifying plausible sets of behavioral rules in agent-based models, rather than a single point estimate.
2025
Garibay, I., Barham, C., Abdidizaji, S., Jayalath, C.
Advances in Artificial Intelligence Applications in Industrial and Systems Engineering (eds. G. Salvendy, V. G. Duffy, W. Karwowski), pp. 355–370, Wiley, 2025. ISBN 978-1-394-25706-5
A book chapter surveying future directions and applications of artificial intelligence in industrial and systems engineering contexts.
2024
Abdidizaji, S., Baekey, A., Jayalath, C., Mantzaris, A., Garibay, O., Garibay, I.
International Conference on Advances in Social Networks Analysis and Mining (ASONAM), pp. 124–138, Springer Nature Switzerland
Uses transfer entropy and multiplex network measures to analyze how credibility and popularity shape news-sharing dynamics on X (Twitter).
2024
Champon, X., Jayalath, C., Rand, W., Jasser, J., Garibay, I., Garibay, O.
57th Annual Hawaii International Conference on System Science (HICSS)
Applies functional data analysis methods to compare behavioral patterns across different social media communities.
2023
Jayalath, C., Gunaratne, C., Rand, W., Senevirathna, C., Garibay, I.
Advances in Complex Systems, 26(02), 2350005 (World Scientific)
Proposes a unified model generalizing threshold-based and probability-based approaches to information diffusion.
2022
Garibay, O., Yousefi, N., Aslett, K., Baggio, J., Hemberg, E., Jayalath, C., Mantzaris, A., Miller, B., O'Reilly, U., Rand, W., Senevirathna, C., Garibay, I.
2022 IEEE 8th International Conference on Collaboration and Internet Computing (CIC), pp. 38–44, IEEE
Characterizes influence pathways across traditional and social media using entropy-based measures.
2021
Garibay, I., Oghaz, T., Yousefi, N., Mutlu, E., Schiappa, M., Scheinert, S., Anagnastopoulos, G., Bouwens, C., Fiore, S., Mantzaris, A., Murphy, J., Rand, W., Salter, A., Stanfill, M., Sukthankar, G., Baral, N., Fair, G., Gunaratne, C., Hajiakhoond, N., Jasser, J., Jayalath, C., Newton, O., Saadat, S., Seneviratna, C., Winter, R., Zhang, X.
Proceedings of the 2019 International Conference of The Computational Social Science Society of the Americas, pp. 153–169, Springer International Publishing
Presents the Deep Agent framework for studying the dynamics of information spread and evolution in social networks.
2021
Baral, N., Gunaratne, C., Jayalath, C., Rand, W., Senevirathna, C., Garibay, I.
Proceedings of the 2019 International Conference of The Computational Social Science Society of the Americas, pp. 265–275, Springer International Publishing
Shows that negative gradients in influence lower the information-processing capacity of social networks.
2021
Senevirathna, C., Gunaratne, C., Rand, W., Jayalath, C., Garibay, I.
Entropy, 23(2), 160
Characterizes behavioral influence patterns in social media cascades using entropy-based measures.
2020
Gunaratne, C., Baral, N., Rand, W., Garibay, I., Jayalath, C., Senevirathna, C.
Computational and Mathematical Organization Theory, 26, 255–276
Examines how information overload affects the dynamics of online conversations.
2019
Gunaratne, C., Baral, N., Rand, W., Garibay, I., Jayalath, C., Senevirathna, C.
arXiv preprint
Proposes a theory of extended working memory to explain patterns in online conversation dynamics.
2019
Senevirathna, C., Gunaratne, C., Jayalath, C., Baral, N., Garibay, I.
Computational Social Science Society of the Americas (CSSSA), Santa Fe, NM
Presents evidence of influence hierarchies among participants in GitHub's cryptocurrency community.
2019
Gunaratne, C., Senevirathna, C., Jayalath, C., Baral, N., Rand, W., Garibay, I.
5th International Conference on Computational Social Science
Introduces the Multi-Action Cascade Model (MACM), in which each action type exerts a distinct influence on the receiver — the founding publication behind the DARPA SocialSim simulation work.
2016
Jayalath, C., Wimalaratne, S. P. W., Karunananda, A. S.
International Journal of Simulation Modelling, 15(4), 585–596
Models goal selection for characters in primary groups within agent-based crowd simulations. The work came out of Chathura's undergraduate thesis (B.Sc., University of Colombo, 2014).
—In preparation
Jayalath, C., Rand, W., Garibay, I.
In preparation
Applies conformal prediction to certify plausible behavioral rule sets in agent-based models of residential segregation.
—In preparation
Jayalath, C., Champon, X., Rand, W., Senevirathna, C., Garibay, I.
In preparation
Quantifies how network clustering coefficient affects outcomes of information diffusion models.
—In preparation
Jayalath, C., Champon, X., Dickey, D., Rand, W., Garibay, I.
In preparation
Investigates how the growth patterns of information cascades relate to the stability of an influencer's position over time.
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