A theoretical and corpus linguistics study of the light verb constructions: Empirical data from Indonesian
  • Metaadatok
Tartalom: https://doktori.bibl.u-szeged.hu/id/eprint/12606/
Archívum: SZTE Doktori Értekezések Repozitórium
Gyűjtemény: Tudományterületek = Bölcsészettudományok: Nyelvtudományok
Típus = Disszertáció
Cím:
A theoretical and corpus linguistics study of the light verb constructions: Empirical data from Indonesian
Létrehozó:
Nugraha Danang Satria
Dátum:
2025-06-23
Téma:
06.02.06. Nyelvészet
06.02.06.01. Formális, kognitív, funkcionális és számítógépes nyelvészet
Tartalmi leírás:
This dissertation investigates Indonesian Light Verb Constructions (LVCs) through the integrated lenses of theoretical linguistics and corpus-based analysis. The primary part of the study provides an empirical foundation, drawing on four corpora to assess the frequency and distribution of LVCs. K-means clustering reveals three natural groupings (low-, medium-, and high-frequency), with Hypothesis 1 supported by significant cross-corpus rank consistency (Spearman’s rs = 0.891, p <.001), validating the temporal and genre-stable nature of LVC frequency patterns. Hypothesis 2 confirms a significant deviation from Zipfian expectations, aligning more closely with Zipf–Mandelbrot law. Additional modeling supports the Menzerath–Altmann law (morpheme-based fit), while vocabulary dynamics are elaborated through Heaps’ Law and Baayen’s productivity metrics. Lexical drift is capture diachronically via Yule’s K and KL Divergence, while entropy measures underscore shifting lexical concentration. A contrastive analysis with Altmann’s (1967) seminal dictionary-based lexical model of Indonesian reveals substantial structural divergence in morpheme density, type distribution, and correlation behavior. Hypothesis 3 is confirmed through morpho-semantic-syntactic stratification across clusters, identifying a structurally asymmetric, gradiently layered LVC system. The secondary part classifies verb elements into True Light Verbs and Vague Action Verbs using aktionsart diagnostics. Machine learning (Naïve Bayes and Random Forest) highlights frequency and semantic parameters as strong predictors of verb productivity. The final part analyzes noun components, distinguishing stative and eventive types based on temporal features. Findings indicate that stative interpretations are largely noun-driven, while eventive reading emerge from verb-noun interaction and distributional patterns. This research offers a theoretically informed, data-driven typology of Indonesian LVCs, contributing to corpus linguistics and the broader modeling of LVC systems in underdescribed languages.
Nyelv:
angol
angol
magyar
angol
Típus:
Disszertáció
NonPeerReviewed
Formátum:
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text
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Azonosító:
Nugraha Danang Satria A theoretical and corpus linguistics study of the light verb constructions: Empirical data from Indonesian. Doktori értekezés, Szegedi Tudományegyetem (2000-). (2025)
Kapcsolat: