Corpus linguistics for leadership studies: Bridging the quantitative-qualitative divide
展示了如何用语料库语言学方法分析领导力相关的大规模文本数据（如CEO演讲、媒体报道），通过Sketch Engine软件对《泰晤士报》中733位高管的领导力定义进行定量与定性结合分析，为领导力研究、教学和实践提供可操作的行为证据。
Our aim in this paper is to add to the methodological toolbox of qualitative research in leadership by illustrating how corpus linguistics (CL) can be used to study large-scale datasets comprised of text or talk. CL differs from other approaches to analysing large-scale textual data, such as topic modeling and sentiment analysis, because it enables detailed quantitative and qualitative analysis of linguistic choices on the level of vocabulary and grammar. CL can be used to study text or talk produced by leaders (such as CEO speeches, letters to shareholders, or interviews) or written about leaders (such as newspaper or magazine articles, social media posts, or biographies). Whilst CL methods can be applied using R or Python, here we demonstrate how a user-friendly proprietary software, Sketch Engine, can be used. We illustrate the relative strengths of the method using a corpus of media texts comprising leader profiles published in The Times (UK) newspaper where senior executives (n = 733) answered the question “What does leadership mean to you?”. We conclude by discussing the potential that CL offers for informing future research and theory development, spanning positivist, interpretivist and social constructionist styles of theorizing. We also outline the practical benefits the method offers for improving leadership practice and for people involved in leadership teaching and training by providing robust evidence about concrete and learnable behaviors.