The present paper was intended to examine the research trends in English for Specific Purposes (ESP) using python and text mining. For this purpose, data were first collected from domestic and foreign theses as well as academic journals published between 1990 and 2019 and available on Research Information Sharing Service (RISS). Then keywords from the titles of the studies were extracted and analyzed via text mining. The study revealed that (1) Both domestic and foreign studies seemed to share much in common in terms of their favored research topics in ESP-text communication, English for Academic Purposes (EAP), and course/curriculum design; (2) Corpus/needs analyses were most favored in Korean ESP studies, while genre/needs analyses and case studies were in foreign ESP studies; (3) 'Engineering' was the field of study most dealt with in both domestic and foreign EAP research; and (4) Not all trends in the same period coincide in domestic and foreign ESP studies. Finally, the present study offered future directions derived from the results of the study.

I. 서론
II. 이론적 배경
    1. 특수목적영어(English for Specific Purposes, ESP)
    2. ESP 관련 연구 동향분석 국내 선행연구
    3. 파이썬(Python)
    4. 텍스트 마이닝
III. 연구 방법
    1. 데이터 수집 대상 및 도구
    2. 데이터 분석 도구
    3. 연구 방법 및 절차
IV. 연구 결과
    1. 국내논문 제목에 대한 텍스트 마이닝 분석 결과
    2. 해외 연구논문 제목에 대한 텍스트 마이닝 분석결과
V. 논의 및 결론
참고문헌

• 권은영(육군사관학교) | Kwon Eun-Young