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.
Articles from the international conference (PDF) at SpringerLink: https://link.springer.com/content/pdf/10.1007%2F978-3-030-23584-0.pdf
Semantic Scholar: https://api.semanticscholar.org/CorpusID:198343523
Deviatkin D., Shelmanov A., Larionov D. Discovering, Classification, and Localization of Emergency Events via Analyzing of Social Network Text Streams // International Conference on Data Analytics and Management in Data Intensive Domains. – Springer, Cham, 2018. – p. 180-196.