SearcharxivSearch

arXiv subjects

Yeonji Seo

Publications and source records attributed to Yeonji Seo.

2 recordsLinked to original sources

Editorial Trajectories in Wikipedia Reflect Underlying Hyperlink Structure

Wikipedia hyperlinks have primarily been studied as navigational tools for readers, but their role in how information providers move between articles during editing remains less explored. Here, we combine the hyperlink network among English Wikipedia articles with editorial histories to examine how article-to-article structure is associated with editors' transitions between articles. We first address the temporal aspect of edit transitions by showing that transitions between hyperlinked article pairs have shorter inter-event times (IETs) than those between non-hyperlinked pairs, indicating that connected articles are effectively closer in editing sequences. We then turn to the structural organization of editing behavior by coarse-graining the hyperlink network into 19 topical communities and measuring editors' topical diversity. Finally, we bring the temporal and structural views together by comparing each editor's transition network with the corresponding hyperlink subnetwork using Jaccard similarity. Combining the measures allows us to distinguish three editor types: 'Specialists' are characterized by focused editing within limited topical domains and transition patterns more closely aligned with the hyperlink structure (low topical diversity, shorter mean IETs, and higher Jaccard similarity), whereas 'generalists' cover broader topics and show weaker similarity to the hyperlink structure (high topical diversity, longer mean IETs, and lower Jaccard similarity). 'Bots' show a distinct algorithm-driven behavior, with low Jaccard similarity and the shortest mean IETs, a combination departing from human-editor patterns despite their often high topical diversity. Such findings demonstrate that the hyperlink structure is not just a static scaffold for reader navigation, but is observationally linked to the sequential organization of editorial activity in collaborative knowledge systems.

physics.soc-ph

Statistical properties of COVID-19 transmission intervals in Republic of Korea

A transmission interval for an infectious disease is important to understand epidemic processes in complex networks. The transmission interval is defined as a time interval between one person's infection and their infection to another person. To study statistical properties of transmission intervals, we analyze a COVID-19 dataset of confirmed cases in Republic of Korea that has been collected for two years since the confirmation of the first case on 19 January 2020. Utilizing demographic information of confirmed individuals, such as sex, age, residence location, and the nature of relation between infectors and infectees, we find that transmission intervals are rarely affected by sexes, but they tend to have larger values for the youngest and oldest age groups than other groups. We also find some metropolitan cities or provinces with relatively larger (smaller) transmission intervals than other locations. These empirical findings might help us to better understand dynamical mechanisms of epidemic processes in complex social systems.

physics.soc-ph