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Social Media Driven Big Data Analysis for Disaster Situation Awareness: A Tutorial
Ieee Transactions on Big Data ; 9(1):1-21, 2023.
Article in English | Web of Science | ID: covidwho-2310263
ABSTRACT
Situational awareness tries to grasp the important events and circumstances in the physical world through sensing, communication, and reasoning. Tracking the evolution of changing situations is an essential part of this awareness and is crucial for providing appropriate resources and help during disasters. Social media, particularly Twitter, is playing an increasing role in this process in recent years. However, extracting intelligence from the available data involves several challenges, including (a) filtering out large amounts of irrelevant data, (b) fusion of heterogeneous data generated by the social media and other sources, and (c) working with partially geo-tagged social media data in order to deduce the needs of the affected people. Spatio-temporal analysis of the data plays a key role in understanding the situation, but is available only sparsely because only a small fraction of people post relevant text and of those very few enable location tracking. In this paper, we provide a comprehensive survey on data analytics to assess situational awareness from social media big data.
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Full text: Available Collection: Databases of international organizations Database: Web of Science Language: English Journal: Ieee Transactions on Big Data Year: 2023 Document Type: Article

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Full text: Available Collection: Databases of international organizations Database: Web of Science Language: English Journal: Ieee Transactions on Big Data Year: 2023 Document Type: Article