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A Research of Corpus-based Medical Humanistic Emotional Vocabulary Analysis
Thu, April 9, 7:45 to 9:15am PDT (7:45 to 9:15am PDT), Los Angeles Convention Center, Floor: Level Two, Poster Hall - Exhibit Hall AAbstract
This paper aims to focus on utilizing sentiment analysis tools imported from the NLTK library in Python to analyze English essays on medical humanities topics by students majoring in clinical medicine and nursing at a Medical University in the context of increasing doctor-patient conflicts and corruption and utilitarianism in the healthcare industry in China. The analysis results are presented in the form of tables and word clouds. Data statistics show a predominance of positive emotions related to the essay topics, accompanied by a simultaneous lack of empathy in medical humanities. The study achieves an interpretation of the emotional aspects of medical humanities texts for English learners in medical schools, providing some guidance for the selection of content in medical humanities courses.