An ensemble model to optimize modularity in dynamic bipartite networks
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DOI: 10.1007/s13198-022-01633-1
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- Diana Purwitasari & Chastine Fatichah & Surya Sumpeno & Christian Steglich & Mauridhi Hery Purnomo, 2020. "Identifying collaboration dynamics of bipartite author-topic networks with the influences of interest changes," Scientometrics, Springer;Akadémiai Kiadó, vol. 122(3), pages 1407-1443, March.
- Zhang, Peng & Wang, Jinliang & Li, Xiaojia & Li, Menghui & Di, Zengru & Fan, Ying, 2008. "Clustering coefficient and community structure of bipartite networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 387(27), pages 6869-6875.
- Alessandro Chessa & Irene Crimaldi & Massimo Riccaboni & Luca Trapin, 2014. "Cluster analysis of weighted bipartite networks: a new copula-based approach," Working Papers 3/2014, IMT School for Advanced Studies Lucca, revised Apr 2014.
- Zhou, Cangqi & Feng, Liang & Zhao, Qianchuan, 2018. "A novel community detection method in bipartite networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 492(C), pages 1679-1693.
- Henriette Heer & Lucas Streib & Ralf B Schäfer & Stefan Ruzika, 2020. "Maximising the clustering coefficient of networks and the effects on habitat network robustness," PLOS ONE, Public Library of Science, vol. 15(10), pages 1-16, October.
- Arthur, Rudy, 2020. "Modularity and projection of bipartite networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 549(C).
- Alessandro Chessa & Irene Crimaldi & Massimo Riccaboni & Luca Trapin, 2014. "Cluster Analysis of Weighted Bipartite Networks: A New Copula-Based Approach," PLOS ONE, Public Library of Science, vol. 9(10), pages 1-12, October.
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Keywords
Dynamic networks; Bipartite modularity; One-mode projection; Communities; Clustering coefficient;All these keywords.
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