Exploring Frequently Occurring Nouns in Business News and Articles Published in Pakistani Newspapers: A Synchronic Corpus-Based Study

Autor: Muhammad Amjad, Riaz Hussain, Zahoor Hussain
Jazyk: angličtina
Rok vydání: 2023
Předmět:
Zdroj: Corporum, Vol 6, Iss 2, Pp 102-114 (2023)
Druh dokumentu: article
ISSN: 2617-2917
2707-787X
Popis: This is a synchronic study with an exploratory corpus-based research design. The objective of the study is to explore and discuss frequently occurring nouns used in the business news and articles published in Pakistani newspapers in 2023. Two corpora containing 403 business news and121 business articles were compiled. Texts were randomly selected from online versions of two Pakistani English newspapers namely Dawn and The Express Tribune. AntConc was used for the identification of frequently occurring nouns in the two corpora. The top 45 nouns in each corpus were selected for analysis and discussion. The word Pakistan topped both lists. A total of 31 words were common in both lists. In the corpus of business news, the words tax (477) and IMF (452) appeared together with minimal frequency difference. This shows a tight link between the Pakistani tax system with IMF policies. The words such as inflation, oil, debt and trade also appeared in the same corpus. Interestingly, the words PTI and Khan also appeared in the top forty-five nouns extracted from contemporary business English texts. No other party or its head could make the place in the given list.Prominent nouns in the corpus of business articles were IMF, debt, growth, inflation, tax, investments, prices, exports, China, GDP, increase, trade and development. The word China appeared 90 times which implies that China is playing a vibrant role in the economy and development of Pakistan.
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