User Reactions About Wildfires on Twitter

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dc.contributor.authorYayla, Ridvan
dc.contributor.authorBilgin, Turgay Tugay
dc.date.accessioned2026-02-12T21:02:48Z
dc.date.available2026-02-12T21:02:48Z
dc.date.issued2022
dc.departmentBursa Teknik Üniversitesi
dc.description1st International Congress of Electrical and Computer Engineering, ICECENG 2022 -- 2022-02-09 through 2022-02-12 -- Bandirma -- 277759
dc.description.abstractForests are the most important part of nature that provides the global balance within the ecosystem. Therefore, wildfires are one of the natural disasters that mostly affect the ecological balance. As an interdisciplinary study, the aim of this study is to measure the reactions of users by classifying comments about wildfires on Twitter with machine learning methods and to investigate the measures against wildfires. In the study, the user comments on wildfires were used on Twitter, which is used by all segments of the society and provides data analysis. A pre-processing has been firstly made for the comments about wildfires by performing word-based text analysis. Sentiment analysis has been realized as positive, negative, and neutral. Moreover, each sentiment group has been evaluated by dividing into four mostly expressed categories. The classification model accuracies have been compared by analyzing with the standard statistical scales. In the study, 58% of Twitter users wish that the wildfires would be ended immediately, approximately 34% of users think that firefighting related to government is enough, 7% of users think that the firefighting is insufficient. Moreover, all Twitter users have frequently referred to firefighting, global warming, support, and sabotage probability in their comments for wildfires. This research supported with sentiment analysis, reveals that wildfires create an alarming situation for all segments of society and it is necessary to act together against wildfires. © 2022, ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering.
dc.identifier.doi10.1007/978-3-031-01984-5_1
dc.identifier.endpage14
dc.identifier.isbn9783032068170
dc.identifier.isbn9783032019035
dc.identifier.isbn9783031969430
dc.identifier.isbn9783031944413
dc.identifier.isbn9783032105530
dc.identifier.isbn9783032014719
dc.identifier.isbn9783642039775
dc.identifier.isbn9783031717154
dc.identifier.isbn9783319737119
dc.identifier.isbn9783030955304
dc.identifier.issn1867-8211
dc.identifier.scopus2-s2.0-85130213430
dc.identifier.scopusqualityQ4
dc.identifier.startpage3
dc.identifier.urihttps://doi.org/10.1007/978-3-031-01984-5_1
dc.identifier.urihttps://hdl.handle.net/20.500.12885/6529
dc.identifier.volume436 LNICST
dc.indekslendigikaynakScopus
dc.language.isoen
dc.publisherSpringer Science and Business Media Deutschland GmbH
dc.relation.ispartofLecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering, LNICST
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanı
dc.snmzKA_Scopus_20260212
dc.subjectMachine learning
dc.subjectSentiment analysis
dc.subjectWildfires
dc.titleUser Reactions About Wildfires on Twitter
dc.typeConference Object

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