Python SnowNLP 활용 색채어 ‘黃’의 감정 분석 연구

Abstract

‘黃’ is a color term used globally, translated as ‘Yellow’ in English and ‘노란색’ in Korean. While the basic meaning of ‘黃’ carries a neutral emotional connotation, an examination of sentences containing ‘黃’ collected from the corpus(CCL) reveals a range of emotional tones, including positive and negative sentiments, in addition to neutral ones. This paper employs SnowNLP, a Python library for Chinese natural language processing(NLP), to conduct a quantitative sentiment analysis of the color term ‘黃’, while simultaneously performing a qualitative analysis of the mechanisms behind its semantic extension from its basic meaning. SnowNLP, utilized for sentiment analysis, is a Python library specifically designed for Chinese natural language processing, capable of performing sentiment analysis on Chinese text. The analysis results show that out of 500 sentences, 176(35.2%) expressed negative sentiment, 274(54.8%) positive sentiment, and 50(10%) neutral sentiment. Shen Jiaxuan (2004:250) noted that language changes not by itself, but through people's use of language. This implies that people reflect, propagate, and utilize their thoughts through language for more effective communication. This study demonstrates the close relationship between language, the tool of communication, and the socio-cultural context in which communication occurs. While ‘黃’ in its basic sense as a color term exhibits neutral emotional connotations, it has acquired both positive and negative meanings in specific social and cultural contexts. In ancient China, it symbolized honor and power, but in modern times, influenced by Western culture, its meaning has extended to include sensational and negative connotations. Beyond these socio-cultural factors, this study also observed semantic extension based on metaphorical meanings.