Associate Professor at The Catholic University of Korea; statistical physics and complex systems; co-author of "Bursty Human Dynamics" (Springer, 2018); http://h2jo.xyz; visiting the University of Michigan till February 2027
Hang-Hyun Jo
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Our new preprint is out on arXiv: Jiyoung Kang, Hang-Hyun Jo, Naoki Masuda, Quantifying concurrency in event-based temporal network and hypergraph data arxiv.org/abs/2605.24633
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 participate in multiple...
I summarized such connections in my paper: arxiv.org/abs/1709.05150
Hang-Hyun Jo
Chapter 15: @kristinalerman.bsky.social on the Strong Friendship Paradox.
Showing how the structure of social networks systematically biases our perceptions of reality. When our friends are not representative of the population, rare behaviours and opinions can appear surprisingly common.
Alex Vespignani officially opening #NetSci2026, reviewing the history of this community's growth
This year, 800 people came together!!
@netscisociety.bsky.social @netsciconf.bsky.social
www.youtube.com/watch?v=MwFe... Yesterday I happened to watch Prof. C.-K. Peng's lecture video. He developed the DFA and MSE, etc. with his colleagues.
Complexity in time series were measured using various methods. Interestingly many of them show power-law behaviors. It's been known that the power-law exponents of power spectral density, autocorrelation function and Hurst exponent (which is itself a power-law exponent) are all connected.
brunch.co.kr/@socph/22
I learned the Detrended Fluctuation Analysis (DFA) in the lecture on econophysics at KAIST in 2006, leading to a JKPS paper. And I coauthored a PLOS ONE paper in 2021 (doi.org/10.1371/jour...) where we applied the multiscale entropy (MSE) method to the temporal network time series data.
Taha Yasseri
Since I got to know the MSE, I've wondered the mathematical relation between MSE and autocorrelation function (ACF) because both measure long-term temporal correlations. Of course they're different; the MSE is based on the entropy, while the ACF is not. I guess there must be some work on this topic.
