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.

Авторы
Deviatkin D.2 , Shelmanov A.2, 1 , Larionov D. 2, 3
Издательство
Springer Verlag
Язык
Английский
Страницы
180-196
Статус
Опубликовано
Том
1003
Год
2019
Организации
  • 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
Ключевые слова
Event detection; Monitoring; Named entity recognition; Novel topic; Text processing; Topic modelling
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