Research theme 02
How do interactions among individuals produce diffusion, influence, and collective dynamics?
Directed information flow through a network
This is the line of research I began my doctoral work in: how do individual behaviors — sharing, ignoring, amplifying — aggregate into population-level patterns of diffusion and influence? My dissertation, Models of Information Diffusion and the Role of Influence, examined how local behavioral rules and network structure shape the spread of information through a system.
That question scaled into large, multi-institution research through the DARPA SocialSim program, where I built simulation infrastructure spanning several social media platforms and co-developed the Multi-Action Cascade Model, and later through the DARPA Modeling Influence Pathways (MIPS) initiative, where I led the design of a transfer-entropy-based dashboard for identifying influence pathways between and within online communities. Across these projects, the throughline is the same: connecting a behavioral premise about how influence operates to a system that can measure or reproduce it at scale.
Projects
SocialSim investigated computational approaches to modeling and forecasting online social behavior. My work centered on a multi-platform simulation framework and the Multi-Action Cascade Model, connecting behavioral assumptions about influence with scalable implementation.
Read the project ↗This line of work studies how information spreads through social systems and how influence can be measured across actors and communities. It spans my doctoral research, diffusion models, and DARPA MIPS work on influence pathways using transfer entropy and network-based methods.
Read the project ↗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.
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).
2023
Jayalath, C., Gunaratne, C., Rand, W., Senevirathna, C., Garibay, I.
Advances in Complex Systems
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.
2020
Jayalath, C., Gunaratne, C., Rand, W., Senevirathna, C., Garibay, I.
Tenth International Conference on Complex Systems (poster session)
Poster examining the final states reached by information diffusion processes on directed scale-free networks.
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.
2019
Senevirathna, C., Gunaratne, C., Jayalath, C., Baral, N., Garibay, I.
Conference of the Computational Social Science Society of the Americas (CSS), Santa Fe, NM (poster session)
Poster examining hidden patterns in influence hierarchies within GitHub's cryptocurrency community.
2019
Jayalath, C., Gunaratne, C., Senevirathna, C., Garibay, I.
5th International Conference on Computational Social Science, Amsterdam, NL (poster session)
Poster establishing a path-dependent equivalence between the Independent Cascade Model and the Linear Threshold Model of diffusion.
—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., Dicky, 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.