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Rumors detection on Social Media during Crisis Management
Claire Laudy
author
2017
Iscram
Albi, France
English
Social Media monitoring has become a major issue in crisis and emergencies management. Indeed, social media may ease the sharing of information between citizens and Public Safety Organizations, but it also enables the rapid spreading of inaccurate information. As information is now provided and shared by anyone to anyone, information credibility is a major issue. We propose an approach to detect rumor in social media. This paper describes our work on semantic graph based information fusion, enhanced with uncertainty management capabilities. The uncertainty management capability enables managing the dierent level of credibility of actors of an emergency (dierent PSO oÿcers and citizens). Functions for information synthesis, conflicting information detection and information evaluation were developed and test during experimentation campaigns. The synthesis and conflicting information detection functionalities are very welcome by end-users. However, the uncertainty management is a combinatorial approach which remains a limitation for use with large amount of information.
Semantic information fusion
Uncertainty management
Ontology
Graph matching
conflict detection
rumors detection
exported from refbase (http://idl.iscram.org/show.php?record=2050), last updated on Mon, 25 Nov 2019 14:35:30 +0100
text
http://idl.iscram.org/files/clairelaudy/2017/2050_ClaireLaudy2017.pdf
ClaireLaudy2017
Proceedings of the 14th International Conference on Information Systems for Crisis Response And Management
Iscram 2017
Tina Comes
F
B
editor
14th International Conference on Information Systems for Crisis Response And Management
2017
Iscram
Albi, France
conference publication
623
632
2411-3387
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