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Lexical Profile of Newspapers Revisited: A Corpus-Based Analysis
The present study analyzed the vocabulary profile of the News on the Web (NOW) corpus, which contained 12 billion words from online newspapers and magazines in 20 countries to determine the vocabulary knowledge needed to reasonably understand online newspaper and magazine articles. The results showe...
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Frontiers Media S.A.
2022
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8907927/ https://www.ncbi.nlm.nih.gov/pubmed/35282246 http://dx.doi.org/10.3389/fpsyg.2022.800983 |
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author | Ha, Hung Tan |
author_facet | Ha, Hung Tan |
author_sort | Ha, Hung Tan |
collection | PubMed |
description | The present study analyzed the vocabulary profile of the News on the Web (NOW) corpus, which contained 12 billion words from online newspapers and magazines in 20 countries to determine the vocabulary knowledge needed to reasonably understand online newspaper and magazine articles. The results showed that, in general, knowledge of the most frequent 4,000 word families in the British National Corpus/Corpus of Contemporary American English (BNC/COCA) wordlist plus proper nouns, marginal words, transparent compounds and acronyms was necessary to gain 95% coverage for the NOW corpus. However, when it came to the 98% coverage, online newspaper and magazine articles from different countries had relatively distinct lexical demands. In-depth analyses were carried out and the findings offered comprehensive insights into the issue. Implications for teaching and learning were also provided. |
format | Online Article Text |
id | pubmed-8907927 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-89079272022-03-11 Lexical Profile of Newspapers Revisited: A Corpus-Based Analysis Ha, Hung Tan Front Psychol Psychology The present study analyzed the vocabulary profile of the News on the Web (NOW) corpus, which contained 12 billion words from online newspapers and magazines in 20 countries to determine the vocabulary knowledge needed to reasonably understand online newspaper and magazine articles. The results showed that, in general, knowledge of the most frequent 4,000 word families in the British National Corpus/Corpus of Contemporary American English (BNC/COCA) wordlist plus proper nouns, marginal words, transparent compounds and acronyms was necessary to gain 95% coverage for the NOW corpus. However, when it came to the 98% coverage, online newspaper and magazine articles from different countries had relatively distinct lexical demands. In-depth analyses were carried out and the findings offered comprehensive insights into the issue. Implications for teaching and learning were also provided. Frontiers Media S.A. 2022-02-24 /pmc/articles/PMC8907927/ /pubmed/35282246 http://dx.doi.org/10.3389/fpsyg.2022.800983 Text en Copyright © 2022 Ha. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Psychology Ha, Hung Tan Lexical Profile of Newspapers Revisited: A Corpus-Based Analysis |
title | Lexical Profile of Newspapers Revisited: A Corpus-Based Analysis |
title_full | Lexical Profile of Newspapers Revisited: A Corpus-Based Analysis |
title_fullStr | Lexical Profile of Newspapers Revisited: A Corpus-Based Analysis |
title_full_unstemmed | Lexical Profile of Newspapers Revisited: A Corpus-Based Analysis |
title_short | Lexical Profile of Newspapers Revisited: A Corpus-Based Analysis |
title_sort | lexical profile of newspapers revisited: a corpus-based analysis |
topic | Psychology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8907927/ https://www.ncbi.nlm.nih.gov/pubmed/35282246 http://dx.doi.org/10.3389/fpsyg.2022.800983 |
work_keys_str_mv | AT hahungtan lexicalprofileofnewspapersrevisitedacorpusbasedanalysis |