A CORPUS-BASED ANALYSIS OF THE MOST FREQUENT ADJECTIVES IN ACADEMIC TEXTS

• Authors: Kartal Galip
• Languages of publication: EN

Abstracts

EN

Based on a mega corpus, The Corpus of Contemporary American English (COCA), this study aims to determine the most frequent adjectives used in academic texts and to investigate whether these adjectives differ in frequency and function in social sciences, technology, and medical sciences. It also identifies evaluative adjectives from a list of a hundred most frequently used adjectives. A total of 839 adjectives, which comprises the list of frequently used adjectives in COCA, were searched using a search engine. 334 of the adjectives were found to appear more frequently in the academic sub-corpus than in other sub-corpora (spoken, fiction, magazine, and newspaper). There was only one adjective that was used more frequently in technology and medical sciences than in social sciences. Some adjectives were very dominant in a specific discipline of academic texts. The frequency of evaluative adjectives in most frequently used 100 adjectives was also listed. It is found that almost 40% percent of the adjectives are evaluative. The results of the study were discussed in terms of frequency effects in language learning and writing in the foreign language as providing learners with corpus data may improve language knowledge and the correct use of adjectives.

Keywords

EN

Data-Driven Learning; corpus linguistics; COCA

• Publisher: IATEFL Poland Computer Special Interest Group & University of Nicosia
• Journal: Teaching English with Technology
• Year: 2017
• Volume: 17
• Issue: 3
• Pages: 3-18

Contributors

author

Kartal Galip

• Necmettin Erbakan University

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