Linguistic Summarization for Analyzing Earthquake Impact: A Study on 2023 Kahramanmaraş Earthquakes in Türkiye

Year 2025, Early View, 1 - 1

Sena Aydoğan , Nazmiye Eligüzel

Abstract

A disaster is an event or a series of events that greatly disrupt the usual flow of daily activity. The earthquakes that struck Kahramanmaraş in 2023 impacted eleven provinces across Türkiye. These earthquakes resulted in the deaths of over 50,000 individuals, caused destruction to more than 500,000 structures including communication and energy facilities, and resulted in substantial economic damages. This study investigated the possible use of linguistic summarization to analyze 11 provinces located in an earthquake-prone area, using data that is peculiar to these provinces. The aim of the study is to transform raw data into intricate descriptions that exhibit linguistic complexity, employing a specific technique known as linguistic summarization. The objective of this research is to examine patterns in each province by taking into account various factors, including the proportion of earthquake-affected provinces in the gross domestic product (GDP) and subsectors data, the total number of buildings in earthquake-affected provinces, data on house damage, data on disaster housing planning, the overall damage to companies by provinces, and data on the damage status of tourism facilities. The main objective of the study is to offer brief and readily understandable information about regions prone to earthquakes, so improving the comprehension of decision-makers and policymakers to enable well-informed decision-making. Analysis indicates that economic recovery may depend on sectors with limited structural damage yet significant GDP contribution, highlighting the necessity of targeted actions to alleviate the enduring effects of disruptions in real estate and the public sector.

Keywords

Earthquake, Fuzzy c-means, Linguistic Summarization

References

• [1] Strategy and Budget Office of the Presidency of the Republic of Türkiye, “Türkiye Presidency Strategy and Budgetary Office,” no. March, 6–7, 2023, [Online]. Available: https://www.sbb.gov.tr/wp-content/uploads/2023/03/2023-Kahramanmaras-and-Hatay-Earthquakes-Report.pdf.
• [2] Akçay, S., Beydili Gürbüz, E., Koca, E., “Trauma Levels After the 2023 Kahramanmaraş Earthquakes in Türkiye”, Journal of Social Service Research, 50(4): 519–530, (2024). DOI: https://doi.org/10.1080/01488376.2024.2339967
• [3] IOM, “2023 Earthquakes Displacement Overview,” 2023, [Online]. Available: https://reliefweb.int/report/turkiye/iom-2023-earthquakes-displacement-overview-turkiye-march-2023.
• [4] Yan, K., Miyajima, M., Kumsar, H., Aydan, Ö., Ulusay, R., Tao, Z., Chen, Y., Wang, F., “Preliminary report of field reconnaissance on the 6 February 2023 Kahramanmaras Earthquakes in Türkiye”, Geoenvironmental Disasters, 11(11), (2024). DOI: https://doi.org/10.1186/s40677-024-00272-x
• [5] Ozkaynak M.I., and Cetin, K.O., “The performance of Karasu Bridge following the February 6, 2023 Kahramanmaras-Turkiye earthquake sequence”, Engineering Geology, 335: 107512, (2024). DOI: https://doi.org/10.1016/j.enggeo.2024.107512
• [6] Yetkin, M., Dedeoğlu, İ.Ö., and Tunç, G., “February 6, 2023, Kahramanmaraş twin earthquakes: Evaluation of ground motions and seismic performance of buildings for Elazığ, southeast of Türkiye”, Soil Dynamics and Earthquake Engineering, 181: 108678, (2024). DOI: https://doi.org/10.1016/j.soildyn.2024.108678
• [7] Toda, S., and Stein, R., “The Role of Stress Transfer in Rupture Nucleation and Inhibition in the 2023 Kahramanmaraş, Türkiye, Sequence, and a One‐Year Earthquake Forecast”, Seismological Research Letters, 95(2A): 596–606, (2024). DOI: https://doi.org/10.1785/0220230252
• [8] Cinar, M., “Utilization of Earthquake Demolition Wastes and Afşin–Elbistan Fly Ash for Soil Improvement after the Kahramanmaraş Earthquake (6 February 2023)”, Sustainability, 16(2): 538, (2024). DOI: https://doi.org/10.3390/su16020538
• [9] Alver Şahin, Ü., and Kaynak, B. “Questioning whether there was a short-term interaction between the 6 February 2023 earthquakes and air quality parameters in Türkiye”, Chemosphere, 347: 140616, (2024). DOI: https://doi.org/10.1016/j.chemosphere.2023.140616
• [10] Yager, R. R., “A new approach to the summarization of data”, Information Sciences, 28(1): 69–86, (1982). DOI: https://doi.org/10.1016/0020-0255(82)90033-0
• [11] Şener Fidan, F., Aydoğan, S., and Akay, D., “Investigating the carbon border adjustment mechanism transition process with linguistic summarization method: A situational analysis of exporting countries”, Advanced Engineering Informatics, 61: 102528, (2024). DOI: https://doi.org/10.1016/j.aei.2024.102528
• [12] Ozturk, D., Aydoğan, S., Kok, I., Akın Bulbul, I., Ozdemir, S., Ozdemir, S., Akay, D., “Linguistic Comparison of Children with and without ASD through Eye-Tracking Data”, In Proceedings of the 2023 9th International Conference on Computer Technology Applications (ICCTA '23). Association for Computing Machinery, New York, NY, USA, 241–246. DOI: https://doi.org/10.1145/3605423.3605457.
• [13] Gilsing, R., Wilbik, A., Grefen, P., Turetken, O., Ozkan, B., Adali, O.E., Berkers, F., “Defining business model key performance indicators using intentional linguistic summaries”, 20(4): 965-996, Springer Berlin Heidelberg, (2021). DOI: https://doi.org/10.1007/s10270-021-00894-x
• [14] Fonseca, B. B., Mar Cornelio, O., and Pupo, I. P., “Linguistic Summarization of Data in Decision-Making on Performance Evaluation”, 2020 XLVI Latin American Computing Conference (CLEI), Loja, Ecuador, 268-274, (2020). DOI: 10.1109/CLEI52000.2020.00038
• [15] Kaczmarek-Majer, K., Rutkowska, A., and Hryniewicz, O., “Evolving membership functions in fuzzy linguistic summarization”, CEUR Workshop Proceedings, 3380, (2022).
• [16] Özdoğan, İ., Boran, F. E., and Akay, D., “A possibilistic approach for interval type-2 fuzzy linguistic summarization of time series”, Artificial Intelligence Review, 54(1): 3991-4018, (2021). DOI: https://doi.org/10.1007/s10462-020-09945-z
• [17] Boran, F. E., and Akay, D., “A generic method for the evaluation of interval type-2 fuzzy linguistic summaries”, IEEE Transactions on Cybernetics, 44(9): 1632–1645, (2014). DOI: https://doi.org/10.1109/TCYB.2013.2291272
• [18] Boran, F. E., Akay, D., and Yager, R. R., “An overview of methods for linguistic summarization with fuzzy sets”, Expert Systems with Applications, 61: 356–377, (2016). DOI: https://doi.org/10.1016/j.eswa.2016.05.044
• [19] Boran, F. E., Akay, D., and Yager, R. R., “A probabilistic framework for interval type-2 fuzzy linguistic summarization”, IEEE Transactions on Fuzzy Systems, 22(6), 1640–1653, (2014). DOI: https://doi.org/10.1109/TFUZZ.2014.2302492
• [20] Zadeh, L., “Fuzzy sets”, Information and Control, 8(3): 338–353, (1965). DOI: https://doi.org/10.1016/S0019-9958(65)90241-X
• [21] Aydoğan, S., Okudan Kremer, G. E., and Akay, D., “Linguistic summarization to support supply network decisions”, Journal of Intelligent Manufacturing, 32(6): 1573–1586, (2021). DOI: https://doi.org/10.1007/s10845-020-01677-9
• [22] Zadeh, L., “A computational approach to fuzzy quantifiers in natural languages”, Computers & Mathematics with Applications, 9(1): 149–184, (1983). DOI: https://doi.org/10.1016/0898-1221(83)90013-5
• [23] Zadeh, L., “PRUF—a meaning representation language for natural languages”, International Journal of Man-Machine Studies, 10: 395–460, (1978). DOI: https://doi.org/10.1016/S0020-7373(78)80003-0
• [24] Boran, F. E., Akay, D., and Yager, R. R., “An overview of methods for linguistic summarization with fuzzy sets”, Expert Systems with Applications, 61: 356–377, (2016). DOI: https://doi.org/10.1016/j.eswa.2016.05.044
• [25] Bezdek, J. C., Ehrlich, R., and Full, W., “FCM: The fuzzy c-means clustering algorithm”, Computers & Geosciences, 10(2-3): 191-203, (1984). DOI: https://doi.org/10.1016/0098-3004(84)90020-7