Investigating Verb-Collocate Patterns in Synonymous Self-Compound Nouns : A Corpus-Based Analysis - Ni Made Ayu Widiastuti; Ni Ketut Sri Rahayuni; Samuel Shaw; Yasmine Aryani Dewi (International Journal of Multilingual Education and Applied Linguistics, 2025)
Understanding verb-noun collocations is essential for exploring how abstract personal qualities are represented in language. This study aims to find out the types of verbs that occur before the five self-related compound nouns (self-esteem, self-confidence, self-assurance, self-worth, and self-respect), and investigate their collocational patterns. The data in this study were obtained from the Corpus of Contemporary American English (COCA). The data were collected by applying the documentation method. The technique involved searching for five compound nouns within the corpus and recording instances of their use. These occurrences, along with their collocates, were then copied and organized in an Excel spreadsheet. In the spreadsheet, columns were adjusted to separate and classify key elements such as the compound noun, the collocating verb, frequency data, and context sentences. The collected data were analyzed qualitatively to provide insights into lexical patterns, the types and tokens of frequency. The results show that the verbs that collocate with five self-related compounds in COCA vary in number and frequency, with self-confidence showing the highest types (20) and self-assurance the lowest (9). The verb build appears most frequently with self-confidence and self-esteem (4 tokens each), suggesting both are viewed as qualities that can be constructed or improved. Self-respect predominantly collocates with have (4 tokens), implying it is seen as possessive, while self-worth reflects both positive and negative framing through increase and reduce (2 tokens each). In contrast, self-assurance is frequently associated with lack (4 tokens) and show (2 tokens), indicating its absence or visibility. These patterns reveal that verb collocates offer important insights into how language frames self-constructions.