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Hang-Hyun Jo

9 papers hereh-index 214 citations11 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • sole author1
  • first author2
  • middle author2
  • last author4

Across the 9 of 9 papers where every author was matched, so the position is known.

fields
  • physics.data-an4
  • physics.soc-ph3
  • cs.SI1
  • physics.comp-ph1
same name
  • Hang-Hyun Jo — 66 papers, h 23
  • Hang-Hyun Jo — 7 papers, h 3
  • Hang-Hyun Jo — 1 paper

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

activity
20242026
most citedBurst-tree structure and higher-order temporal correlations

4 citations · 12 across the 8 of their papers we have counts for

collaborators
Showing 2024Show all

4 papers · 1 filter

physics.data-an2024★ 4 cited

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…

cs.SI2024

Homophilic organization of egocentric communities in ICT services

Chandreyee Roy, Hang-Hyun Jo, János Kertész +2

Members of a society can be characterized by a large number of features, such as gender, age, ethnicity, religion, social status, and shared activities. One of the main tie-forming…

physics.data-an2024★ 4 cited

Temporal scaling theory for bursty time series with clusters of arbitrarily many events

Hang-Hyun Jo, Tibebe Birhanu, Naoki Masuda

Long-term temporal correlations in time series in a form of an event sequence have been characterized using an autocorrelation function (ACF) that often shows a power-law decaying…

physics.soc-ph2024

Exact solutions of the simplified March model for organizational learning

Hang-Hyun Jo

James G. March's celebrated agent-based simulation model for organizational learning [March, Organization Science \textbf{2}, 71 (1991)] has been extensively studied for the last d…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.