Diachronic corpus analysis of stance markers in research articles: The field of applied linguistics

Abstract

Despite the continuously growing body of research on metadiscourse markers in different genres and through various perspectives for over 20 years, very little is known of how these features have evolved over time in response to the historically developing practices of academic communities. Motivated by such an ambition, the current research drew on a corpus of 4.3 million words taken from three leading journals of applied linguistics in order to trace the diachronic evolution of stance markers of research articles from 1996 to 2016. Hyland's model of metadiscourse was adopted for the analysis of the selected corpus. The data were explored using concordance software AntConc. Moreover, a Chi-Square statistical measure was run to determine statistical significances. The analysis revealed a significant decline in the overall frequency of stance markers, with devices in all categories, except self-mention which increased dramatically over the past 20 years. The paper has been concluded by offering some suggestions for teaching academic writing.

Are Academics Becoming More Confused Than Before? A Diachronic Study of Confusion Markers in Applied Linguistics Research Articles

“…Contrary to the decreasing use of boosters in biology found in Hyland and Jiang (2016b), Poole et al’s study revealed divergent trends in the use of epistemic stance markers when a corpus of specialized texts focusing on a particular topic was examined. In a more recent study, Rezaei et al (2021) reported an overall decline in stance features in RAs of applied linguistics except for self-mentions from 1996 to 2016.…”

“…Informed by frame semantics, the Berkeley FrameNet research project (Baker et al, 2003;Ruppenhofer et al, 2010) has annotated semantic frames, their frame elements, and relations between semantic frames for the core English lexicon. Moreover, FrameNet categorizes FEs as core and peripheral ones, with the former referring to those that specify and uniquely define a frame and the latter relating to those that generally characterize a frame (Ruppenhofer et al, 2010).…”

“…Informed by frame semantics, the Berkeley FrameNet research project (Baker et al, 2003;Ruppenhofer et al, 2010) has annotated semantic frames, their frame elements, and relations between semantic frames for the core English lexicon. Moreover, FrameNet categorizes FEs as core and peripheral ones, with the former referring to those that specify and uniquely define a frame and the latter relating to those that generally characterize a frame (Ruppenhofer et al, 2010). Examples 1 and 2, taken from the present corpus and presented in line with FrameNet annotation format, illustrate the Obviousness frame and its FEs evoked by a typical confusion marker, unclear and the Stimulus_focus frame with its FEs evoked by confusing in applied linguistics RAs, respectively.…”

Identifying stance in legislative discourse: a corpus-driven study of data protection laws

“…The manual annotation or identification of stance markers is a time-consuming process, which makes corpus analysis the most convenient and, consequently, the most prevalent method for researchers in stance studies. Scholars (e.g., Aull et al 2017;Rezaei et al 2021) employ the corpus as a tool to investigate various stance categories or conduct horizontal and longitudinal comparative studies. The present study, focusing on the stance analysis in data protection laws of the U.S., the EU, and China, appropriately adopts the corpus-driven approach, which shows both sound rationale and practical feasibility.…”