Climate event dataset based on Ukrainian online information space

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dc.citation.epage74
dc.citation.journalTitleІнформація, комунікація, суспільство 2025: ICS-2025 : матеріали XIV Міжнародної наукової конференції
dc.citation.spage73
dc.contributor.affiliationLviv Polytechnic National University
dc.contributor.authorUstianovych, Taras
dc.contributor.authorFedushko, Solomiia
dc.coverage.placenameЛьвів
dc.coverage.placenameLviv
dc.coverage.temporal22-24 травня 2025 року, Львів
dc.date.accessioned2025-06-05T08:08:40Z
dc.date.created2025-05-22
dc.date.issued2025-05-22
dc.description.abstractThe study describes multimodal data collection on climate change and environmental issues from thoroughly selected and reputable Ukrainian Telegram channels using the Aho-Cosarick algorithm. The dataset includes above 5500 records of multiple formats created between 2020 and 2025 and includes war-related publications. A mathematical representation of the data collection process to match the topic of interest is provided.
dc.format.extent73-74
dc.format.pages2
dc.identifier.citationUstianovych T. Climate event dataset based on Ukrainian online information space / Ustianovych Taras, Fedushko Solomiia // Інформація, комунікація, суспільство 2025: ICS-2025 : матеріали XIV Міжнародної наукової конференції, 22-24 травня 2025 року, Львів. — Lviv : Lviv Politechnic Publishing House, 2025. — P. 73–74. — (Системи штучного інтелекту та машинне навчання).
dc.identifier.citationenUstianovych T. Climate event dataset based on Ukrainian online information space / Ustianovych Taras, Fedushko Solomiia // Informatsiia, komunikatsiia, suspilstvo 2025: ICS-2025 : materialy XIV Mizhnarodnoi naukovoi konferentsii, 22-24 travnia 2025 roku, Lviv. — Lviv : Lviv Politechnic Publishing House, 2025. — P. 73–74. — (Systemy shtuchnoho intelektu ta mashynne navchannia).
dc.identifier.isbn978-966-994-052-0
dc.identifier.urihttps://ena.lpnu.ua/handle/ntb/65857
dc.language.isoen
dc.publisherВидавництво Львівської політехніки
dc.publisherLviv Politechnic Publishing House
dc.relation.ispartofІнформація, комунікація, суспільство 2025: ICS-2025 : матеріали XIV Міжнародної наукової конференції, 2025
dc.relation.references[1] Bai, X., Van der Leeuw, S., O’Brien, K., Berkhout, F., Biermann, F., Brondizio, E. S., Cudennec, C., Dearing, J., Duraiappah, A., Glaser, M., Revkin, A., Steffen, W., & Syvitski, J. (2016). Plausible and desirable futures in the Anthropocene: A new research agenda. Global Environmental Change, 39, 351-362. https://doi.org/10.1016/j.gloenvcha.2015.09.017
dc.relation.references[2] Stasio, O.R., Buriak, N.E. (2024). Processing data obtained from different sources to improve safety oriented indicators. Collection of abstracts of the V International Scientific and Practical Conference "Environmental Safety in Warfare", Lviv, November 21, 2024. Lviv: LDUBZhD, 227-229.
dc.relation.references[3] Guo, Y., Qiu, Z., Huang, H., & Siong , C. E. (2023). Improved Keyword Recognition Based on AhoCorasick Automaton. International Joint Conference on Neural Networks (IJCNN), Gold Coast, Australia. 1-7, https://doi.org/10.1109/IJCNN54540.2023.10191315
dc.relation.references[4] Webersinke, N., Kraus, M., Bingler, J. A., & Leippold, M. (2021). ClimateBert: A Pretrained Language Model for Climate-Related Text. ArXiv. https://arxiv.org/abs/2110.12010
dc.relation.references[5] Ferreira, M., Nunes, N., Ceccarini, C., Prandi, C.,and Nisi, V.(2023) The Russia-Ukraine war and climate change: Analysis of one year of data-visualisations, in De Sainz Molestina, D., Galluzzo, L., Rizzo, F., Spallazzo, D. (eds.), IASDR 2023: Life-Changing Design, 9-13 October, Milan, Italy. https://doi.org/10.21606/iasdr.2023.431
dc.relation.referencesen[1] Bai, X., Van der Leeuw, S., O’Brien, K., Berkhout, F., Biermann, F., Brondizio, E. S., Cudennec, C., Dearing, J., Duraiappah, A., Glaser, M., Revkin, A., Steffen, W., & Syvitski, J. (2016). Plausible and desirable futures in the Anthropocene: A new research agenda. Global Environmental Change, 39, 351-362. https://doi.org/10.1016/j.gloenvcha.2015.09.017
dc.relation.referencesen[2] Stasio, O.R., Buriak, N.E. (2024). Processing data obtained from different sources to improve safety oriented indicators. Collection of abstracts of the V International Scientific and Practical Conference "Environmental Safety in Warfare", Lviv, November 21, 2024. Lviv: LDUBZhD, 227-229.
dc.relation.referencesen[3] Guo, Y., Qiu, Z., Huang, H., & Siong , C. E. (2023). Improved Keyword Recognition Based on AhoCorasick Automaton. International Joint Conference on Neural Networks (IJCNN), Gold Coast, Australia. 1-7, https://doi.org/10.1109/IJCNN54540.2023.10191315
dc.relation.referencesen[4] Webersinke, N., Kraus, M., Bingler, J. A., & Leippold, M. (2021). ClimateBert: A Pretrained Language Model for Climate-Related Text. ArXiv. https://arxiv.org/abs/2110.12010
dc.relation.referencesen[5] Ferreira, M., Nunes, N., Ceccarini, C., Prandi, C.,and Nisi, V.(2023) The Russia-Ukraine war and climate change: Analysis of one year of data-visualisations, in De Sainz Molestina, D., Galluzzo, L., Rizzo, F., Spallazzo, D. (eds.), IASDR 2023: Life-Changing Design, 9-13 October, Milan, Italy. https://doi.org/10.21606/iasdr.2023.431
dc.relation.urihttps://doi.org/10.1016/j.gloenvcha.2015.09.017
dc.relation.urihttps://doi.org/10.1109/IJCNN54540.2023.10191315
dc.relation.urihttps://arxiv.org/abs/2110.12010
dc.relation.urihttps://doi.org/10.21606/iasdr.2023.431
dc.rights.holder© Національний університет “Львівська політехніка”, 2025
dc.subjectdataset
dc.subjectmultimodal data
dc.subjectclimate change
dc.subjectdata collection
dc.titleClimate event dataset based on Ukrainian online information space
dc.typeConference Abstract

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