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Twitter Streaming Data Analytics for Disaster Alerts

  • In today's world, disasters, both natural and manmade, are becoming increasingly frequent, and new solutions are of a compelling need to provide and disseminate information about these disasters to the public and concerned authorities in an effective and efficient manner. One of the most frequently used ways for information dissemination today is through social media, and when it comes to real-time information, Twitter is often the channel of choice. Thus, this paper discusses how Big Data Analytics (BDA) can take advantage of information streaming from Twitter to generate alerts and provide information in real-time on ongoing disasters. The paper proposes TAGS (Twitter Alert Generation System), a novel solution for collecting and analyzing social media streaming data in realtime and subsequently issue warnings related to ongoing disasters using a combination of Hadoop and Spark frameworks. The paper tests and evaluates the proposed solution using Twitter data from the 2018 earthquake in Palu City, Sulawesi, Indonesia. The proposed architecture was able to issue alert messages on various disaster scenarios and identify critical information that can be utilized for further analysis. Moreover, the performance of the proposed solution is assessed with respect to processing time and throughput that shows reliable system efficiency.

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Metadaten
Document Type:Part of a Book
Language:English
Author(s):Syed Attique Shah, Sadok Ben Yahia, Keegan McBride, Akhtar Jamil, Dirk Draheim
Parent Title (English):2021 2nd International Informatics and Software Engineering Conference (IISEC)
Publisher:IEEE
Publication year:2021
Publishing Institution:Hertie School
First Page:1
Last Page:6
DOI:https://doi.org/10.1109/IISEC54230.2021.9672370
ISBN:978-1-6654-0759-5
Release Date:2023/02/17
Hertie School Research:Centre for Digital Governance
Licence of document (German):Metadaten / metadata
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