Content Analysis of Medical Research Articles: A corpus-based study

Content analysis applied for comparing texts, a writer’s works with others or the same author, the texts written in a natural language with texts in other languages literature and review of specialized field. The present study aims to analyze the articles to extract the sentences structure in order to support medical researchers. This study investigates 4-word lexical bundles in medical research articles. To this end, a corpus of 2,400,000 words was established based on 33 subject areas in medicine and frequency of 20 and distribution numbers of at least 5 were considered as criterion. Word smith tools 5, Antconc3.23, ABBYY Fine Reader to professional edition were used for the identification of lexical bundles. Then, identified lexical bundles were classified according to their functions and structures in the medical research articles. Totally, 102 lexical bundles with different structures and functions were identified in medical articles. The findings of the current study showed that most of the medical writers use text-oriented bundles in their articles. This study presents new insights in better understanding of medical research articles related to specific area and further researches in written academic discourse and English for Academic Purposes. It also broadens new horizon on areas of text analysis and text statistical assessment.