This paper is in the following e-collection/theme issue:

Theme Issue: Novel Coronavirus (COVID-19) Outbreak Rapid Reports (1520) JMIR Theme Issue: COVID-19 Special Issue (2461) Infectious Diseases (non-STD/STI) (1592) Statistical Methods for Surveillance and Population Health (158)

Published on in Vol 6, No 4 (2020): Oct-Dec

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/24291, first published .
Analysis of the COVID-19 Epidemic Transmission Network in Mainland China: K-Core Decomposition Study

Analysis of the COVID-19 Epidemic Transmission Network in Mainland China: K-Core Decomposition Study

Analysis of the COVID-19 Epidemic Transmission Network in Mainland China: K-Core Decomposition Study

Authors of this article:

Lei Qin1 Author Orcid Image ;   Yidan Wang1 Author Orcid Image ;   Qiang Sun1 Author Orcid Image ;   Xiaomei Zhang1 Author Orcid Image ;   Ben-Chang Shia2 Author Orcid Image ;   Chengcheng Liu3 Author Orcid Image
Article Authors Cited by (5) Tweetations (1) Metrics

Journals

  1. Meyer H, Peach A, Guenther L, Kedar H, Brüggemann M. Between Calls for Action and Narratives of Denial: Climate Change Attention Structures on Twitter. Media and Communication 2023;11(1):278 View
  2. Zhou B, Lv Y, Wang J, Zhang J, Xuan Q. Attacking the Core Structure of Complex Network. IEEE Transactions on Computational Social Systems 2023;10(4):1428 View
  3. Shetty R, Bhattacharjee S, Dutta A, Namtirtha A. GSI: An Influential Node Detection Approach in Heterogeneous Network Using Covid-19 as Use Case. IEEE Transactions on Computational Social Systems 2023;10(5):2489 View
  4. Kroger S, Validi H, Hicks I. Maximizing Engagement in Large-Scale Social Networks. INFORMS Journal on Optimization 2024;6(3-4):196 View