A Bibliometric Analysis of Generative Linguistics: A Study Based on Web of Science Data (1975-2025).
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| Title: | A Bibliometric Analysis of Generative Linguistics: A Study Based on Web of Science Data (1975-2025). |
|---|---|
| Alternate Title: | Üretici Dilbiliminin Bibliyometrik Analizi: Web of Science Verilerine Dayalı Bir Çalışma (1975-2025). |
| Authors: | DOYUMGAC, Ibrahim1 ibrahim63doyum@gmail.com |
| Source: | IZU Journal of Education / İZÜ Eğitim Dergisi. 2025, Vol. 7 Issue 2, p114-144. 31p. |
| Subject Terms: | *Bibliometrics, *Artificial intelligence, *Citation indexes, *Generative grammar, *Concept mapping, Citation networks, Natural language processing |
| People: | Chomsky, Noam, 1928- |
| Abstract (English): | This study is based on a comprehensive bibliometric analysis of 1,908 publications containing the key concept of generative linguistics between 1975 and 2025. The aim of the study is to systematically reveal the temporal trends, thematic orientations, and publication patterns of generative linguistics literature through these publications indexed in the Web of Science database. Performance analysis, conceptual mapping, co-occurrence and co-citation networks, historiographic analysis, and thematic trend analyses were employed in the research. The findings show that generative linguistics gained momentum rapidly after 2010, especially from 2018 onwards, with international visibility reaching its highest level in the period 2021-2024. The field's institutional leaders include the University of Cambridge, Harvard University, the University of Edinburgh, and Stanford University. The US, China, and the UK stand out as the most productive countries. Conceptually, the literature has expanded from classical linguistics topics, such as syntax, grammar, and semantics, to new AI-focused themes, including artificial intelligence, generative AI, ChatGPT, and large language models. This intellectual line, which began with Chomsky's theoretical contributions, has taken a new direction with the emergence of deep learning and natural language processing studies since 2017. In general, generative linguistics is evolving into an interdisciplinary research field that integrates artificial intelligence while maintaining its deep theoretical foundations, and it is expected to exhibit strong growth potential in the coming years. [ABSTRACT FROM AUTHOR] |
| Abstract (Turkish): | Bu araştırma, 1975-2025 yılları arasında üretici dilbilimi anahtar kavramını içeren 1.908 yayına dayalı kapsamlı bir bibliyometrik analiz üzerine kuruludur. Araştırmanın amacı, Web of Science veritabanında dizinlenen bu yayınlar üzerinden, üretici dilbilimi literatürünün zamansal eğilimlerini, tematik yönelimlerini ve yayın örüntülerini sistematik biçimde ortaya koymaktır. Araştırmada performans analizi, kavramsal haritalama, eşzamanlılık ve eşalıntı ağları, tarih yazımı ve tematik eğilim analizleri uygulanmıştır. Bulgular, üretici dilbiliminin 2010'dan sonra, özellikle 2018'den itibaren hızla ivme kazandığını ve uluslararası görünürlüğünün 2021-2024 döneminde en yüksek seviyesine ulaştığını göstermektedir. Bu alandaki kurumsal liderler arasında Cambridge Üniversitesi, Harvard Üniversitesi, Edinburgh Üniversitesi ve Stanford Üniversitesi bulunmaktadır. ABD, Çin ve İngiltere en üretken ülkeler olarak öne çıkmaktadır. Kavramsal olarak literatür, sözdizimi, gramer ve anlambilim gibi klasik dilbilim konularından, yapay zekâ, üretken yapay zekâ, ChatGPT ve büyük dil modelleri gibi yeni yapay zekâ odaklı temalara doğru genişlemiştir. Chomsky’nin teorik katkılarıyla başlayan bu entelektüel çizgi, 2017'den bu yana derin öğrenme ve doğal dil işleme çalışmalarının ortaya çıkmasıyla yeni bir yön almıştır. Genel olarak üretici dilbilim, derin teorik temellerini korurken yapay zekâyı bütünleştiren disiplinler arası bir araştırma alanı olarak gelişmektedir ve önümüzdeki yıllarda güçlü bir büyüme potansiyeli sergilemesi beklenmektedir. [ABSTRACT FROM AUTHOR] |
| Copyright of IZU Journal of Education / İZÜ Eğitim Dergisi is the property of IZU Journal of Education and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Database: | Education Research Complete |
| FullText | Links: – Type: pdflink Text: Availability: 0 |
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| Header | DbId: ehh DbLabel: Education Research Complete An: 191619642 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: A Bibliometric Analysis of Generative Linguistics: A Study Based on Web of Science Data (1975-2025). – Name: TitleAlt Label: Alternate Title Group: TiAlt Data: Üretici Dilbiliminin Bibliyometrik Analizi: Web of Science Verilerine Dayalı Bir Çalışma (1975-2025). – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22DOYUMGAC%2C+Ibrahim%22">DOYUMGAC, Ibrahim</searchLink><relatesTo>1</relatesTo><i> ibrahim63doyum@gmail.com</i> – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22IZU+Journal+of+Education+%2F+İZÜ+Eğitim+Dergisi%22">IZU Journal of Education / İZÜ Eğitim Dergisi</searchLink>. 2025, Vol. 7 Issue 2, p114-144. 31p. – Name: Subject Label: Subject Terms Group: Su Data: *<searchLink fieldCode="DE" term="%22Bibliometrics%22">Bibliometrics</searchLink><br />*<searchLink fieldCode="DE" term="%22Artificial+intelligence%22">Artificial intelligence</searchLink><br />*<searchLink fieldCode="DE" term="%22Citation+indexes%22">Citation indexes</searchLink><br />*<searchLink fieldCode="DE" term="%22Generative+grammar%22">Generative grammar</searchLink><br />*<searchLink fieldCode="DE" term="%22Concept+mapping%22">Concept mapping</searchLink><br /><searchLink fieldCode="DE" term="%22Citation+networks%22">Citation networks</searchLink><br /><searchLink fieldCode="DE" term="%22Natural+language+processing%22">Natural language processing</searchLink> – Name: SubjectPerson Label: People Group: Su Data: <searchLink fieldCode="PE" term="%22Chomsky%2C+Noam%2C+1928-%22">Chomsky, Noam, 1928-</searchLink> – Name: Abstract Label: Abstract (English) Group: Ab Data: This study is based on a comprehensive bibliometric analysis of 1,908 publications containing the key concept of generative linguistics between 1975 and 2025. The aim of the study is to systematically reveal the temporal trends, thematic orientations, and publication patterns of generative linguistics literature through these publications indexed in the Web of Science database. Performance analysis, conceptual mapping, co-occurrence and co-citation networks, historiographic analysis, and thematic trend analyses were employed in the research. The findings show that generative linguistics gained momentum rapidly after 2010, especially from 2018 onwards, with international visibility reaching its highest level in the period 2021-2024. The field's institutional leaders include the University of Cambridge, Harvard University, the University of Edinburgh, and Stanford University. The US, China, and the UK stand out as the most productive countries. Conceptually, the literature has expanded from classical linguistics topics, such as syntax, grammar, and semantics, to new AI-focused themes, including artificial intelligence, generative AI, ChatGPT, and large language models. This intellectual line, which began with Chomsky's theoretical contributions, has taken a new direction with the emergence of deep learning and natural language processing studies since 2017. In general, generative linguistics is evolving into an interdisciplinary research field that integrates artificial intelligence while maintaining its deep theoretical foundations, and it is expected to exhibit strong growth potential in the coming years. [ABSTRACT FROM AUTHOR] – Name: Abstract Label: Abstract (Turkish) Group: Ab Data: Bu araştırma, 1975-2025 yılları arasında üretici dilbilimi anahtar kavramını içeren 1.908 yayına dayalı kapsamlı bir bibliyometrik analiz üzerine kuruludur. Araştırmanın amacı, Web of Science veritabanında dizinlenen bu yayınlar üzerinden, üretici dilbilimi literatürünün zamansal eğilimlerini, tematik yönelimlerini ve yayın örüntülerini sistematik biçimde ortaya koymaktır. Araştırmada performans analizi, kavramsal haritalama, eşzamanlılık ve eşalıntı ağları, tarih yazımı ve tematik eğilim analizleri uygulanmıştır. Bulgular, üretici dilbiliminin 2010'dan sonra, özellikle 2018'den itibaren hızla ivme kazandığını ve uluslararası görünürlüğünün 2021-2024 döneminde en yüksek seviyesine ulaştığını göstermektedir. Bu alandaki kurumsal liderler arasında Cambridge Üniversitesi, Harvard Üniversitesi, Edinburgh Üniversitesi ve Stanford Üniversitesi bulunmaktadır. ABD, Çin ve İngiltere en üretken ülkeler olarak öne çıkmaktadır. Kavramsal olarak literatür, sözdizimi, gramer ve anlambilim gibi klasik dilbilim konularından, yapay zekâ, üretken yapay zekâ, ChatGPT ve büyük dil modelleri gibi yeni yapay zekâ odaklı temalara doğru genişlemiştir. Chomsky’nin teorik katkılarıyla başlayan bu entelektüel çizgi, 2017'den bu yana derin öğrenme ve doğal dil işleme çalışmalarının ortaya çıkmasıyla yeni bir yön almıştır. Genel olarak üretici dilbilim, derin teorik temellerini korurken yapay zekâyı bütünleştiren disiplinler arası bir araştırma alanı olarak gelişmektedir ve önümüzdeki yıllarda güçlü bir büyüme potansiyeli sergilemesi beklenmektedir. [ABSTRACT FROM AUTHOR] – Name: AbstractSuppliedCopyright Label: Group: Ab Data: <i>Copyright of IZU Journal of Education / İZÜ Eğitim Dergisi is the property of IZU Journal of Education and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.) |
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| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.46423/izujed.1373845 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 31 StartPage: 114 Subjects: – SubjectFull: Bibliometrics Type: general – SubjectFull: Artificial intelligence Type: general – SubjectFull: Citation indexes Type: general – SubjectFull: Generative grammar Type: general – SubjectFull: Concept mapping Type: general – SubjectFull: Citation networks Type: general – SubjectFull: Natural language processing Type: general – SubjectFull: Chomsky, Noam, 1928- Type: general Titles: – TitleFull: A Bibliometric Analysis of Generative Linguistics: A Study Based on Web of Science Data (1975-2025). Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: DOYUMGAC, Ibrahim IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 07 Text: 2025 Type: published Y: 2025 Identifiers: – Type: issn-print Value: 26677938 Numbering: – Type: volume Value: 7 – Type: issue Value: 2 Titles: – TitleFull: IZU Journal of Education / İZÜ Eğitim Dergisi Type: main |
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