Cross-Linguistic Analysis of Light Verb Constructions: Collocational Patterns in Persian and English - Qiqi Guan (International Journal of Education and Humanities, 2025)
Light Verb Constructions (LVCs) have garnered considerable attention in linguistic research, yet the study of co-selection between verbs and nouns within LVCs from a cross-linguistic perspective remains underexplored. This study addresses the interaction between LVC components, mainly focusing on Persian, which features a unique marginal verb structure that collates with specific nouns. This structure is similar to light verb constructions in English, though differences exist in the two languages' collocational patterns and lexical selection. Therefore, this research aims to analyze the collocational relationships within LVC components in Persian and English, identifying commonalities and distinct characteristics across these languages. The methodology employed in this study is corpus-based cross-linguistic analysis, utilizing a comparative approach to examine the collocational patterns between verbs and nouns in Persian and English LVCs. Data were drawn from linguistic corpora for each language and then analyzed to identify co-selection patterns and the underlying semantic relationships. The findings reveal a significant co-selection relationship between nouns and their constructions in LVCs across both languages, although the specific patterns vary according to each language's context. These results indicate that collocations within LVCs influence syntactic structure and affect semantic relationships and cross-linguistic understanding. This study highlights the importance of lexical co-selection in LVCs for cross-linguistic research, which, in turn, may deepen insights into the interaction between different languages. Extend cross-linguistic analysis to include a broader range of languages and explore contextual factors influencing co-selection in LVCs. This can benefit fields such as translation, foreign language learning, and the development of natural language processing technologies.