activity
20242026
collaborators

8 papers

physics.soc-ph2026

Quantifying concurrency in event-based temporal network and hypergraph data

Jiyoung Kang, Hang-Hyun Jo, Naoki Masuda

Many social, biological, and technological systems are recorded as sequences of time-stamped interactions. In such systems, concurrency, i.e., the tendency for an individual to par…

physics.soc-ph2026

Modeling non-Poissonian temporal hypergraphs by Markovian node dynamics

Hang-Hyun Jo, Naoki Masuda

Temporal hypergraphs capture time-resolved group interactions among nodes. Empirical data support that time-stamped group interactions show bursty event sequences and non-trivial t…

physics.data-an2025

Analysis framework for higher-order temporal correlations with applications to human heartbeats

Tibebe Birhanu, Hang-Hyun Jo

We propose a time series analysis framework focused on higher-order temporal correlations in the event sequence beyond the interevent time distribution by employing the burst-tree…

physics.data-an2025

Maximum likelihood estimation of burst-merging kernels for bursty time series

Tibebe Birhanu, Hang-Hyun Jo

Various time series in natural and social processes have been found to be bursty. Events in the time series rapidly occur within short time periods, forming bursts, which are alter…

physics.comp-ph2025

Analysis of the autocorrelation function for time series with higher-order temporal correlations: An exponential case

Min-ho Yu, Hang-Hyun Jo

Temporal correlations in the time series observed in various systems have been characterized by the autocorrelation function. Such correlations can be explained by heavy-tailed int…

physics.data-an2024

Burst-tree structure and higher-order temporal correlations

Tibebe Birhanu, Hang-Hyun Jo

Understanding characteristics of temporal correlations in time series is crucial for developing accurate models in natural and social sciences. The burst-tree decomposition method…