Abstract
Growth is a concept of particular interest for economic discourse. This paper sets out to explore a small corpus of economic growth, which consists of articles from The Economist. The corpus software used in this study is a web-based tool Wmatrix, an automatic tagging software able to assign semantic field (domain) tags, and to permit the extraction of key words and key semantic domains by applying the keyness calculation to tag frequency lists. The results show that at 99% confidence (or p < 0.01), the cut-off of 6.63 (log likelihood value) indicates that there are 1051 positive keywords (including multiword expressions) and 80 key semantic domains generated from the corpus. It is evident that BRICs or the emerging economies/markets, in particular China and India, are a big concern regarding economic growth over the past years. A number of examples of possible ways forward in teaching methodology are presented.
Highlights
There has been a growing literature on the economic discourse over the past three decades
This paper sets out to explore a small corpus of economic growth, which consists of articles from The Economist
The results show that at 99% confidence, the cut-off of 6.63 indicates that there are 1051 positive keywords and 80 key semantic domains generated from the corpus
Summary
There has been a growing literature on the economic discourse over the past three decades. Some studies have dealt with the linguistic and discursive aspects of the widely read masterworks: Adam Smith’s The Wealth of Nations (Bazerman, 1993; Henderson, 2006), Marshall’s Elements of Economics (Del Lungo Camiciotti, 2005), and Keynes’ General Theory (Bondi, 2010). While research on economic discourse can be based on researchers’ intuitive knowledge (Tribe, 2015), there are a growing interest in corpus approaches to social sciences. Unlike previous studies that are mainly concerned with growth metaphor (Crawford Camiciottoli, 2007; Henderson, 1994; White, 2003), this paper aims to explore discourse of economic growth by conducting keyness analysis with the aid of corpus tool Wmatrix
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