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A Study on the Most Frequent Academic Words in High Impact Factor English Nursing Journals: A Corpus-based Study.
Iranian Journal of Nursing and Midwifery Research 2019 January
Background: The ability to comprehend a text depends primarily on the knowledge about its words. This study investigated the most frequent words in high impact factor (IF) English nursing journals.
Materials and Methods: This corpus-based study was conducted on the articles of 13 English nursing journals with an IF of over 0.7 from November 2014 to September 2016. After the typographical errors were corrected and the tokens (running words) in each journal were equalized, the tokens were analyzed using the Range software. Finally, a word list was extracted from the final 2851 articles and 8196,953 tokens to reach the optimal 98% vocabulary coverage.
Results: A word list consisting of 1081 word families and 3175 word types with 5.24% coverage was extracted, which fulfilled the 98% vocabulary coverage. In other words, the coverage of the 1081 word-family list (5.24%), the coverage of the 1st 3000 English word families (87.55%), proper names, marginal words, compound words, and abbreviations related to the software (3.29%), and the coverage of the new proper names (1.13%), new compounds (0.02%), new abbreviations (0.72%), and letter-number combinations (0.05%) totaled 98%.
Conclusions: By learning the 1st 3000 English word families and the 1081 word families introduced in this study, a nursing student can comprehend the texts of articles in high IF nursing journals without any considerable help from other resources.
Materials and Methods: This corpus-based study was conducted on the articles of 13 English nursing journals with an IF of over 0.7 from November 2014 to September 2016. After the typographical errors were corrected and the tokens (running words) in each journal were equalized, the tokens were analyzed using the Range software. Finally, a word list was extracted from the final 2851 articles and 8196,953 tokens to reach the optimal 98% vocabulary coverage.
Results: A word list consisting of 1081 word families and 3175 word types with 5.24% coverage was extracted, which fulfilled the 98% vocabulary coverage. In other words, the coverage of the 1081 word-family list (5.24%), the coverage of the 1st 3000 English word families (87.55%), proper names, marginal words, compound words, and abbreviations related to the software (3.29%), and the coverage of the new proper names (1.13%), new compounds (0.02%), new abbreviations (0.72%), and letter-number combinations (0.05%) totaled 98%.
Conclusions: By learning the 1st 3000 English word families and the 1081 word families introduced in this study, a nursing student can comprehend the texts of articles in high IF nursing journals without any considerable help from other resources.
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