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Author (down) Sooji Han; Fabio Ciravegna pdf  isbn
  Title Rumour Detection on Social Media for Crisis Management Type Conference Article
  Year 2019 Publication Proceedings of the 16th International Conference on Information Systems for Crisis Response And Management Abbreviated Journal Iscram 2019  
  Volume Issue Pages  
  Keywords Rumours, large-scale data, event summarisation, sub-event detection, social media analysis  
  Abstract We address the problem of making sense of rumour evolution during crises and emergencies. We study how

understanding and capturing emerging rumours can benefit decision makers during such event. To this end, we

propose a two-step framework for detecting rumours during crises. In the first step, we introduce an algorithm to

identify noteworthy sub-events in real time. In the second step, we introduce a graph-based text ranking method

for summarising newsworthy sub-events while events unfold. We use temporal and content-based features to

achieve the effective and real-time response and management of crises situations. These features can improve

efficiency in the detection of key rumours in the context of a real-world application. The effectiveness of our

method is evaluated over large-scale Twitter data related to real-world crises. The results show that our framework

can efficiently and effectively capture key rumours circulated during natural and human-made disasters.
  Address The University of Sheffield, United Kingdom  
  Corporate Author Thesis  
  Publisher Iscram Place of Publication Valencia, Spain Editor Franco, Z.; González, J.J.; Canós, J.H.  
  Language English Summary Language English Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 2411-3387 ISBN 978-84-09-10498-7 Medium  
  Track T8- Social Media in Crises and Conflicts Expedition Conference 16th International Conference on Information Systems for Crisis Response and Management (ISCRAM 2019)  
  Notes Approved no  
  Call Number Serial 1860  
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