Electronic Thesis and Dissertation Repository

Degree

Master of Arts

Program

Education

Supervisor

Dr. Stuart Webb

Abstract

A seven-million-word newspaper corpus that was made up of approximately 7,600 newspaper articles posted to The New York Times website between June, 2015 and October, 2016 was created and analyzed to identify the technical vocabulary of a newspaper and determine its lexical coverage. The results showed that there were 405 technical words of the newspaper as a whole that accounted for 9.76% of the running words in the NYT corpus, and an average of 748 technical words of each newspaper section with an average lexical coverage of 23.82%. Identifying the technical vocabulary of a newspaper is valuable for language learners, because leaning these words before reading articles may help to reduce the vocabulary burden. The findings also indicated that reading newspapers from the same section is likely to be more effective to learn vocabulary than reading articles randomly.


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