Araştırma Makalesi
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Deprem Sonrası Twitter'daki Yıkılan Bina İhbarlarının Doğrulanması: Türkiye'den Bir Örnek Olay

Yıl 2023, Cilt: 5 Sayı: 2, 77 - 84, 25.12.2023
https://doi.org/10.56130/tucbis.1316898

Öz

6 Şubat 2023 tarihinde Türkiye'de 11 şehrin bulunduğu geniş bir bölgede hasarlara sebep olan ve resmi rakamlara göre 50 binden fazla kişinin hayatını kaybettiği çok yüksek şiddetli 2 deprem meydana gelmiştir. 11 şehri etkileyen bu çaptaki bu felakette, arama-kurtarma faaliyetleri için, altında canlıların olduğu enkazları tespit etmek önemli bir problemdir. Ancak buradaki bir diğer, doğru/gerçek adreslerin elde edilmesidir. Adresleri ihbar edebilmek için kendisi ya da yakınları enkaz altında olan kişiler geleneksel iletişim yöntemleri denemişlerdir. Yaşanan hat problemleri, afetzedeleri internet bazlı iletişim yöntemlerine sevk etmiştir. Bu noktada, çok kısa bir sürede milyonlara bilgi ulaştırma gücüyle sosyal medya devreye girmiştir. Ancak, sosyal medyanın bu etkisi sahte haberlerden dolayı ciddi infial olasılığını da beraberinde getirmektedir. Bu çalışmada, Twitter üzerinden depremden sonraki ilk 24 saatte atılan tweetlerle bir analiz yapılmıştır. Öncelikle, enkaz ihbarı içeren tweetler tespit edilmiş ve metin ayrıştırma yöntemleri ile ilgili adres bilgileri alınmıştır. Bu adreslerin koordinatlarında gerçek bir yıkım olma durumu ise deprem sonrası alınan İHA görüntüleri üzerinden teyit edilmiştir. Sonuç olarak, sosyal medyada en çok yayılan 100 ihbardaki adreslerde veya 100 metre yakınında bir yıkım olma doğruluğu %90 olarak görülmüştür. İhbarlardan tespit edilemeyen çok sayıda adres ise Türkiye’de kullanılan adres sisteminin ne kadar yanlış olduğunu da göstermiştir.

Kaynakça

  • Avdar, R., & Avdar, R. (2022). Socio-Economic Effects of Natural Disasters in Turkey. Journal of Disaster and Risk, 5(1), 1–12. https://doi.org/10.35341/afet.1032084
  • Kankanamge, N., Yigitcanlar, T., Goonetilleke, A., & Kamruzzaman, M. (2020). Determining disaster severity through social media analysis: Testing the methodology with South East Queensland Flood tweets. International Journal of Disaster Risk Reduction, 42, 101360. https://doi.org/10.1016/j.ijdrr.2019.101360
  • Kılıç, B., & Gülgen, F. (2019). Determination of Consistency Levels in Postal Address Information Used in Turkey. Harita Dergisi-in Turkish, 161, 26–34.
  • Larson, J. (2023). Tweet Flash - Twitter Scraper. Apify. Retrieved 4 June 2023, from https://apify.com/shanes/tweet-flash
  • MacIntyre, A. G., Barbera, J. A., & Smith, E. R. (2012). Surviving collapsed structure entrapment after earthquakes: A “Time-to-Rescue” analysis. Prehospital and Disaster Medicine, 21(1), 4–17. https://doi.org/10.1017/S1049023X00003253
  • Nekoei-Moghadam, M., & Savabi, J. (2021). Role of social media in earthquake: A systematic review. Iranian Red Crescent Medical Journal, 23(5). https://doi.org/10.32592/ircmj.2021.23.5.447
  • Öztürkçü, T., & Suri, L. (2020). The Creation of address information systems. Istanbul Commerce University Journal of Tecnologies and Applied Sciences, 2(2), 25–34.
  • Türk, T. (2008). Integrating address registraition system with urban information systems. Journal of Geodesy and Geoinformation, (99), 13–22.
  • Ulutaş Karakol, D., Ataman, S., & Cömert, Ç. (2021). An Investigation on spatial address registration system: The case of Ordu province. Afyon Kocatepe University Journal of Science and Engineering, 21(1), 179–195. https://doi.org/10.35414/akufemubid.804036
  • Yılmaz, G., & Demiröz Yıldırım, S. (2020). Methods Used in Urban Search and Rescue in Disasters and Evaluation of Current Approaches. Journal of Natural Hazards and Environment 6(1), 196–208. https://doi.org/10.21324/dacd.533639

Verifying reports of collapsed buildings from twitter aftermaths of earthquakes: A case study from Turkey

Yıl 2023, Cilt: 5 Sayı: 2, 77 - 84, 25.12.2023
https://doi.org/10.56130/tucbis.1316898

Öz

On February 6, 2023, two highly severe earthquakes occurred in a wide region encompassing 11 cities in Turkey, resulting in extensive damage and an official death toll exceeding 50,000. In the aftermath of this catastrophic event that affected multiple cities, identifying the locations of debris with potential survivors became a crucial challenge for search and rescue operations. However, another significant obstacle emerged in obtaining accurate and genuine addresses. Individuals who were either trapped themselves or had relatives under the collapsed buildings attempted to report addresses using conventional communication methods. Communication difficulties on lines prompted disaster victims to resort to internet-based communication methods. Consequently, social media platforms emerged as powerful tools for rapidly disseminating information to millions of people. However, alongside the positive impact of social media, the risk of generating significant panic due to the spread of fake news also surfaced. This study analyzes tweets posted on Twitter within the first 24 hours following the earthquakes. Firstly, tweets containing reports of collapsed structures were identified, and text parsing techniques were employed to extract address information. The veracity of destruction at these addresses was confirmed using imagery captured from Unmanned Aerial Vehicles (UAVs) in the aftermath of the earthquakes. As a result, a 90% accuracy rate was observed in confirming the presence of destruction either at the reported addresses or within a 100-meter proximity, based on the top 100 most widely shared reports on social media. Moreover, the presence of numerous unidentifiable addresses highlights the necessity for continued enhancements to the Address Registration System.

Kaynakça

  • Avdar, R., & Avdar, R. (2022). Socio-Economic Effects of Natural Disasters in Turkey. Journal of Disaster and Risk, 5(1), 1–12. https://doi.org/10.35341/afet.1032084
  • Kankanamge, N., Yigitcanlar, T., Goonetilleke, A., & Kamruzzaman, M. (2020). Determining disaster severity through social media analysis: Testing the methodology with South East Queensland Flood tweets. International Journal of Disaster Risk Reduction, 42, 101360. https://doi.org/10.1016/j.ijdrr.2019.101360
  • Kılıç, B., & Gülgen, F. (2019). Determination of Consistency Levels in Postal Address Information Used in Turkey. Harita Dergisi-in Turkish, 161, 26–34.
  • Larson, J. (2023). Tweet Flash - Twitter Scraper. Apify. Retrieved 4 June 2023, from https://apify.com/shanes/tweet-flash
  • MacIntyre, A. G., Barbera, J. A., & Smith, E. R. (2012). Surviving collapsed structure entrapment after earthquakes: A “Time-to-Rescue” analysis. Prehospital and Disaster Medicine, 21(1), 4–17. https://doi.org/10.1017/S1049023X00003253
  • Nekoei-Moghadam, M., & Savabi, J. (2021). Role of social media in earthquake: A systematic review. Iranian Red Crescent Medical Journal, 23(5). https://doi.org/10.32592/ircmj.2021.23.5.447
  • Öztürkçü, T., & Suri, L. (2020). The Creation of address information systems. Istanbul Commerce University Journal of Tecnologies and Applied Sciences, 2(2), 25–34.
  • Türk, T. (2008). Integrating address registraition system with urban information systems. Journal of Geodesy and Geoinformation, (99), 13–22.
  • Ulutaş Karakol, D., Ataman, S., & Cömert, Ç. (2021). An Investigation on spatial address registration system: The case of Ordu province. Afyon Kocatepe University Journal of Science and Engineering, 21(1), 179–195. https://doi.org/10.35414/akufemubid.804036
  • Yılmaz, G., & Demiröz Yıldırım, S. (2020). Methods Used in Urban Search and Rescue in Disasters and Evaluation of Current Approaches. Journal of Natural Hazards and Environment 6(1), 196–208. https://doi.org/10.21324/dacd.533639
Toplam 10 adet kaynakça vardır.

Ayrıntılar

Birincil Dil İngilizce
Konular Coğrafi Bilgi Sistemleri ve Mekansal Veri Modelleme, Doğal Afetler
Bölüm Araştırma Makaleleri
Yazarlar

Abdulkadir Şeker 0000-0002-4552-2676

Erken Görünüm Tarihi 18 Aralık 2023
Yayımlanma Tarihi 25 Aralık 2023
Yayımlandığı Sayı Yıl 2023 Cilt: 5 Sayı: 2

Kaynak Göster

APA Şeker, A. (2023). Verifying reports of collapsed buildings from twitter aftermaths of earthquakes: A case study from Turkey. Türkiye Coğrafi Bilgi Sistemleri Dergisi, 5(2), 77-84. https://doi.org/10.56130/tucbis.1316898

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