過去20年來，世界面臨許多經濟不確定性和金融危機，備受全球關注。各國都把經濟穩定當作首要任務。 2019年COVID-19危機發生時，不僅全球經濟嚴重衰退，而且對國家、社會和國際產生持久和深遠的影響。本論文是以語料庫方法研究「金融危機」一詞及與其相關主題之詞彙。語料庫包括《經濟學人》英文週刊2012年至 2021年1,200 篇文章、1,183,166 字。有三個研究問題：(一)、目標詞「危機」的頻率分佈及其與從2012至2021年世界GDP成長率關係為何？ (二)、兩個語料庫中高頻核心內容詞為何？它們有何不同？ (三)、兩個語料中高頻核心否定內容詞「CRISIS」、「INFLATION」、「RECESSION」、「CRASH」和「DISASTER」的搭配為何？它們有何不同？數據分析採用定量和定性方法。結果提供了兩個語料庫中經濟相關領域和政治相關領域的高頻核心內容詞的大量資訊。結果也顯示危機(CRISIS)和衰退(RECESSION)在統計上具有顯著的線性關係。危機(CRISIS)和崩潰(CRASH)之間也存在統計上顯著的線性關係。但結果並未預測GDP成長率與危機發生頻率之間的關係有顯著差異，可能受到樣本數（年）的干擾。

Over the past 20 years, the world has faced many economic uncertainties and financial crises that have attracted much global attention. Every country considers economic stability as its top task. When the COVID-19 crisis occurred, it not only involved disease control and crisis management, but it also had lasting and far-reaching effects on countries, society and international cooperation. The present study investigated the phrase “financial crisis” and the lexical association of topics related to financial crises. In this study, I aimed to analyze the collected corpus of the Economist articles from 2012 to 2021, comprising 1,200 articles, 1,183,166 running words to investigate the lexical associations of the word “CRISIS” and its synonyms. The research questions are: a) What is the frequency distribution of the target word “CRISIS”? and what is its relationship with the world GDP growth rate from 2012 to 2021? b) What are the high frequency core content words in the two corpora? And how do they differ? c) What are the core collocations of the high frequency negative words “CRISIS,” “INFLATION,” “RECESSION,” “CRASH,” and “DISASTER” in the two corpuses. And how do they differ? Both quantitative and qualitative method were applied in the data analysis. The results provide a great deal of information on the high frequency core content words in the two corpuses from the economic- and political-related fields. The results also indicate that crisis and recession have a statistically significant linear relationship, while crisis and crash have a statistically significant linear relationship. However, the result did not predict that the relation between the GDP growth rate and the frequency of crisis is significantly different; this may have been due to interference by the number sample (years).

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