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dc.contributor.authorEroğlu, Yunus
dc.date.accessioned2023-12-14T11:03:23Z
dc.date.available2023-12-14T11:03:23Z
dc.date.issued2023en_US
dc.identifier.citationEroglu, Y. (2023). Text Mining Approach for Trend Tracking in Scientific Research: A Case Study on Forest Fire. Fire 2023, 6(1), Article number 33. https://doi.org/10.3390/fire6010033en_US
dc.identifier.urihttps://doi.org/10.3390/fire6010033
dc.identifier.urihttps://hdl.handle.net/20.500.12508/2661
dc.description.abstractScientific studies are increasing day by day with the development of technology. Today, more than 171 billion academic records are made available to researchers via the Web of Science database, which is frequently followed by the scientific community, and is where records of articles, proceedings, and books in many different fields are kept. More than 40 thousand studies are reached when a search is made for research on forest fires in the relevant database. It is unfeasible to examine and read so many publications and understand what topics are important in the relevant field, what is trending, or whether there is a difference between the subjects studied based on years and/or regions/countries. The most effective and scientific method of deriving information from such large and unstructured data is text mining. In this study, text mining is used to reveal where the research on forest fires in the Web of Science database concentrates, which study topics have emerged, how an issue's level of importance changes over the years, and which topics different countries focus on. Therefore, the abstracts of approximately 32 thousand articles published in English were collected and analyzed based on the country of the authors and the published years. Over 600 words in the abstracts were indexed for each article and their importance was calculated according to inverse document frequency. A size reduction was made to determine the main concepts of the articles by using the singular value decomposition and a total of 29 different concepts were found. Among these, important concepts can be mentioned such as damage to vegetation and species affected, post-fire actions, fire management, and post-fire structural changes. Considering all the articles, studies on soil, fuel (biofuel), treatment, emissions, and species were found to be important. The results we have obtained in this study are by no means a summary of the research carried out in the field; they do, however, allow statistical due diligence concerning, for example, which subjects are important in the relevant field, the determination of increasing and decreasing trending topics, which countries attach importance to in the same research, and so on. Thus, it will function as be a guide in terms of the direction, timing, and budget allocation of research plans in a specific area in the future.en_US
dc.language.isoengen_US
dc.publisherMDPIen_US
dc.relation.isversionof10.3390/fire6010033en_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.subjectForest fireen_US
dc.subjectText miningen_US
dc.subjectTopic extractionen_US
dc.subjectTrend analysisen_US
dc.subject.classificationElectrical Engineering, Electronics & Computer Science - Transportation - Airlines
dc.subject.classificationAircraft
dc.subject.classificationAirline Industry
dc.subject.classificationAirfare
dc.titleText Mining Approach for Trend Tracking in Scientific Research: A Case Study on Forest Fireen_US
dc.typearticleen_US
dc.relation.journalFireen_US
dc.contributor.departmentMühendislik ve Doğa Bilimleri Fakültesi -- Endüstri Mühendisliği Bölümüen_US
dc.identifier.volume6en_US
dc.identifier.issue1en_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.contributor.isteauthorEroğlu, Yunus
dc.relation.indexWeb of Science - Scopusen_US
dc.relation.indexWeb of Science Core Collection - Science Citation Index


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