Corpus-based Multi-dimensional Analysis of the Register Features of Financial News - Li, Shoulin (International Journal of Social Sciences and Public Administration, 2024)
Nowadays, people rely heavily on financial news media to get financial updates. But as is well known, for non-native speakers of English, in order to fully understand such news, they also need to learn some register features of such financial news besides adequate English language knowledge. The purpose of this study is to explore and analyze the linguistic features of English financial news, and to help readers effectively understand financial news. Specifically, this study employes multi-feature/multi-dimensional analysis (henceforth MF/MD) method to analyze the register characteristics of English financial news based on the theory of register. Through analyzing the self-compiled corpus of financial news, it is found that that the financial news has four major register features: interactivity, persuasion, information and professionalism. These findings will shed lights on the understanding of financial news as well as the learning and teaching of financial/business English.