Producing Better Disaster Management Plan in Post-Disaster Situation Using Social Media Mining
| Autor: | Soumya Banerjee, Sounak Sadhukhan, Prasun Das, Arun Kumar Sangaiah |
|---|---|
| Rok vydání: | 2018 |
| Předmět: |
Emergency management
Situation awareness Flood myth business.industry Context (language use) 02 engineering and technology Plan (drawing) Contextual design Social media mining 020204 information systems 0202 electrical engineering electronic engineering information engineering 020201 artificial intelligence & image processing Social media business Environmental planning |
| DOI: | 10.1016/b978-0-12-813314-9.00009-8 |
| Popis: | Any type of disaster significantly impact on death troll and damage of wealth and properties. However, as the threats and impact of disaster become global, and therefore to accomplish a mere optimal disaster management plan could reduce the post disaster effect. The multi-dimensions and trends of disaster data usher the possibility of analyzing the context and situation awareness and in turn it is being instrumental to collect, refer and infer about multiple accumulation of post disaster responses. Emerging social media and network is remarkably well compatible towards intelligent data centric system, which, fosters to release an effective disaster management plan under post disaster scenario. This paper is pointing the contextual data mining from social media and also describes the social media as sensor of data source. Indian State Chennai, experienced with vulnerable flood disaster has been presented as case study for the analysis. |
| Databáze: | OpenAIRE |
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