Trends in genre analysis articles on scientific abstract structures: A Quantitative content analysis

Abstract

Genre analysis is a methodologically prominent approach to segmenting a scientific abstract into discourse units. Genre analysis studies on scientific abstract structures have valuable outputs not only for secondary information services, including bibliographic databases and online services but also for scientific communication and library and information science (LIS) education. However, trends of research on this topic have not been investigated yet. This study identifies research trends and reveals knowledge gaps and research opportunities in genre analysis articles on scientific abstracts. For this purpose, Web of Science and Scopus databases were searched to identify the articles. According to the study selection criteria, 75 articles were included in the quantitative content analysis. It was found that the most frequently studied genres were research articles (73.3%), proceedings (%12), and thesis/dissertations (8%). The sample size of the corpus ranged from 5 to 4214 abstracts ( M = 223.8, MD = 94, SD = 523.8). The authors most frequently cited for abstract genre models were Hyland, Swales, and Santos, respectively. In 18.7% of articles, at least one of the abstract standards was cited. Approximately, two-thirds of the articles were comparative. Languages (44.7%), disciplines (25.5%), genres, and native/non-native authors (8.5%) were compared most frequently. English was the most frequently studied language, both individual (72.4%) and comparatively (25.9%). The results of this study suggest that the LIS community, as well as applied linguistics, can seize the opportunity to address gaps in academic genres, disciplines, and languages. In addition, future studies are expected to have generalizable results to assist the scientific communication and LIS communities.