Discovering, Classification, and Localization of Emergency Events via Analyzing of Social Network Text Streams

We present text processing framework for discovering, classification, and localization emergency related events via analysis of information sources such as social networks. The framework performs focused crawling of messages from social networks, text parsing, information extraction, detection of messages related to emergencies, automatic novel event discovering, matching them across different sources, as well as event localization and visualization on a geographical map. For detection of emergency-related messages, we use CNN and word embeddings. The components of the framework are experimentally evaluated on Twitter and Facebook data. © 2019, Springer Nature Switzerland AG.

Authors
Deviatkin D.2 , Shelmanov A.2, 1 , Larionov D. 2, 3
Publisher
Springer Verlag
Language
English
Pages
180-196
Status
Published
Volume
1003
Year
2019
Organizations
  • 1 Skolkovo Institute of Science and Technology, Moscow, Russian Federation
  • 2 Federal Research Center “Computer Science and Control” of Russian Academy of Sciences, Moscow, Russian Federation
  • 3 People’s Friendship University of Russia, Moscow, Russian Federation
Keywords
Event detection; Monitoring; Named entity recognition; Novel topic; Text processing; Topic modelling
Date of creation
24.12.2019
Date of change
24.12.2019
Short link
https://repository.rudn.ru/en/records/article/record/55512/
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