Abstract
This diachronic study explores the linguistics phenomena of the verb f-word in English song lyrics across genres and time via various corpus computational tools. This study has three chief objectives; to identify the viability of using computation tools to generate a diachronic corpus across time and genres; second, determine the frequency distributions of f-word, and finally, analyze the uses of f-word in the Diachronic Corpus of English Song Lyrics (DCOESL). Quantitative and qualitative methods were employed for this study. The data were generated and analysed via AntConc, CLAWS part-of-speech taggers and UCREL Semantic Analysis System English tagger. The frequency distributions of f-word and its collocations were then compared to reference corpora; BNC and COCA. Four statistical tests of significance namely Chi-square, Log-likelihood, Mutual Information and t-score were administered to test statistical difference within DCOESL and between the corpora. The findings reveal that corpus computational tools provide a priceless opportunity to test and challenge our existing intuition about the language. More importantly, it has provided an avenue for researchers to explore languages across time. Additionally, the study shows that f-word in English song lyrics experiences ascending trend since the 1980s, with highest occurrences in R&B. It exhibits that the highest occurrences of verb f-word reflects social actions and a high preference for simple present tense, and simple sentence structure. These features have led to a conclusion that song lyrics resemble spoken English, particularly the conversation register.
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