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Journals / Afet ve Risk Dergisi / 2022 / Cilt: 5 Sayı: 2

Decision Support System for Natural Disaster Response Process with Twitter Data

Twitter Verisi İle Doğal Afet Müdahale Süreci İçin Karar Destek Uygulaması

Ozge Doguc(İSTANBUL MEDİPOL ÜNİVERSİTESİ)0000-0002-5971-9218
Pages
408–419
Publication Date
2022-10-31
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AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

The application showed that high risk scores are created for places that were heavily affected by the fire, such as Marmaris Hisarönü and Milas Çökertme.

📌 3 Key Takeaways

🎯
Objective & Hypothesis:In the natural disaster response process, the use of limited resources in place and on time is very important in limiting the loss of life and property.
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Key Findings & Data:Fast and accurate transmission of the shared information to the response teams will benefit the coordination of the effort.
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Conclusion & Impact:The application showed that high risk scores are created for places that were heavily affected by the fire, such as Marmaris Hisarönü and Milas Çökertme.
🔬Design:Araştırma Makalesi
📍Scope:2021 Verileri
⚙️Variables:Doğal Afet Yönetimi · Veri Yönetimi · Veri Madenciliği

Abstract

In the natural disaster response process, the use of limited resources in place and on time is very important in limiting the loss of life and property. Disaster coordination centers are established in order to respond to the disaster in a timely manner and to manage the allocation of resources. During a disaster, individuals and institutions share live information on social media. Fast and accurate transmission of the shared information to the response teams will benefit the coordination of the effort. For this purpose, in this study, a decision support system that generates alerts via SMS and e-mail by processing the tweets published on Twitter with text mining has been introduced. By the decision support system, a content analysis was made for each tweet obtained from Twitter, and along with the location, date and time information, risk scores were calculated. With risk scores renewed every hour, warnings have been created for locations with high scores. In the study, the application of the decision support system was demonstrated with more than 120,000 tweets shared during the forest fires in Manavgat, Marmaris and Milas in July and August 2021. The application showed that high risk scores are created for places that were heavily affected by the fire, such as Marmaris Hisarönü and Milas Çökertme.

Özet

Doğal afetlere müdahale sürecinde kısıtlı kaynakların yerinde ve zamanında kullanılması can ve mal kaybını sınırlamada çok önemlidir. Afete zamanında müdahale etmek ve kaynakları sevkini yönetmek amaçlarıyla afet koordinasyon merkezleri oluşturulur. Afet sırasında, bireyler ve kurumlar sosyal medya üzerinden anlık bilgi verici paylaşımlar yapılmaktadır. Paylaşılan bilginin hızlı ve doğru şekilde afet koordinasyon ekiplerine iletilmesi, ekiplerin yönetimine fayda sağlayacaktır. Bu amaçla, bu çalışmada Twitter üzerinden yapılan paylaşımları metin madenciliği ile işleyerek, SMS ve e-posta ile uyarı oluşturan bir karar destek sistemi tanıtılmıştır. Karar destek sistemi tarafından, Twitter’dan elde edilen her tweet için yer, tarih ve saat bilgisiyle birlikte, içerik analizi yapılmış ve risk puanı hesaplanmıştır. Her saat yenilenen risk puanlarıyla, kritik durumdaki lokasyonlar için uyarı oluşturulmuştur. Çalışmada, 2021 Temmuz ve Ağustos aylarında Manavgat, Marmaris ve Milas’ta çıkan orman yangınları sırasında paylaşılan 120,000’den fazla tweet ile karar destek sisteminin uygulaması gösterilmiştir. Uygulamada, Marmaris Hisarönü, Milas Çökertme gibi yangından çok etkilenen yerler için yüksek risk puanının oluşturulduğu görülmüştür.

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Cite This Article

Doguc, O. (2022). Decision Support System for Natural Disaster Response Process with Twitter Data. Afet ve Risk Dergisi, Cilt: 5 Sayı: 2, 408–419. https://doi.org/10.35341/afet.1144350

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