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Titlebook: Complex Networks XIII; Proceedings of the 1 Diogo Pacheco,Andreia Sofia Teixeira,Giuseppe Mang Conference proceedings 2022 The Editor(s) (i

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发表于 2025-3-21 18:40:19 | 显示全部楼层 |阅读模式
书目名称Complex Networks XIII
副标题Proceedings of the 1
编辑Diogo Pacheco,Andreia Sofia Teixeira,Giuseppe Mang
视频video
概述Contains contributions presented at the 13th International Conference on Complex Networks.Aims to explore and celebrate this interdisciplinary nature of complex networks.Discusses ideas and findings a
丛书名称Springer Proceedings in Complexity
图书封面Titlebook: Complex Networks XIII; Proceedings of the 1 Diogo Pacheco,Andreia Sofia Teixeira,Giuseppe Mang Conference proceedings 2022 The Editor(s) (i
描述.This book contains contributions presented at the 13th International Conference on Complex Networks (CompleNet), April 19–22, 2022. CompleNet is an international conference on complex networks that brings together researchers and practitioners from diverse disciplines—from sociology, biology, physics, and computer science—who share a passion to better understand the interdependencies within and across systems.  CompleNet is a venue to discuss ideas and findings about all types of networks, from biological to technological and to informational and social. It is this interdisciplinary nature of complex networks that CompleNet aims to explore and celebrate..
出版日期Conference proceedings 2022
关键词Conference Proceedings; Graph Theory; Complex Systems; Computer Science; Collective Behaviour; Data Scien
版次1
doihttps://doi.org/10.1007/978-3-031-17658-6
isbn_softcover978-3-031-17660-9
isbn_ebook978-3-031-17658-6Series ISSN 2213-8684 Series E-ISSN 2213-8692
issn_series 2213-8684
copyrightThe Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerl
The information of publication is updating

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Rigmor Texhammar,Roland R. Schmokert fake news. The derived co-attention weights allow our framework to provide the propagation graph-level and news article word-level explanations, respectively. We demonstrate that FND-NUP method outperforms state-of-the-art propagation-based and content-based fake news detection approaches.
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Co-Attention Based Multi-contextual Fake News Detection,t fake news. The derived co-attention weights allow our framework to provide the propagation graph-level and news article word-level explanations, respectively. We demonstrate that FND-NUP method outperforms state-of-the-art propagation-based and content-based fake news detection approaches.
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Correlation Financial Networks of an Unstable Stock Market: Empirical Study,wed stable growth after the 2008 crisis). The main research question of this paper is as follows: do the behavior patterns of market networks for fairly stable financial systems differ from the behavior patterns of networks for volatile systems that are experiencing multiple shocks?
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Conference proceedings 2022nternational conference on complex networks that brings together researchers and practitioners from diverse disciplines—from sociology, biology, physics, and computer science—who share a passion to better understand the interdependencies within and across systems.  CompleNet is a venue to discuss id
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Targeted Attacks on the World Air Transportation Network: Impact on Its Regional Structure,re isolated one after the other from the world air transportation network. Additionally, although the Betweenness attack effectively splits the network, its impact on regional routes is less pronounced.
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