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  • 标题:MeVer NetworkX: Network Analysis and Visualization for Tracing Disinformation
  • 本地全文:下载
  • 作者:Olga Papadopoulou  ; Themistoklis Makedas  ; Lazaros Apostolidis 
  • 期刊名称:Future Internet
  • 电子版ISSN:1999-5903
  • 出版年度:2022
  • 卷号:14
  • 期号:5
  • 页码:147
  • DOI:10.3390/fi14050147
  • 语种:English
  • 出版社:MDPI Publishing
  • 摘要:The proliferation of online news, especially during the “infodemic” that emerged along with the COVID-19 pandemic, has rapidly increased the risk of and, more importantly, the volume of online misinformation. Online Social Networks (OSNs), such as Facebook, Twitter, and YouTube, serve as fertile ground for disseminating misinformation, making the need for tools for analyzing the social web and gaining insights into communities that drive misinformation online vital. We introduce the MeVer NetworkX analysis and visualization tool, which helps users delve into social media conversations, helps users gain insights about how information propagates, and provides intuition about communities formed via interactions. The contributions of our tool lie in easy navigation through a multitude of features that provide helpful insights about the account behaviors and information propagation, provide the support of Twitter, Facebook, and Telegram graphs, and provide the modularity to integrate more platforms. The tool also provides features that highlight suspicious accounts in a graph that a user should investigate further. We collected four Twitter datasets related to COVID-19 disinformation to present the tool’s functionalities and evaluate its effectiveness.
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