어니스트 헤밍웨이 노인과 바다의 네트워크 분석—서사단계에 따른 정서단어를 중심으로
Network Analysis of Ernest Hemingway’s ‘The Old Man and the Sea’ - Focusing on Emotion Words According to Narrative Stages
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This study analyzes the meaning and emotions conveyed in Hemingway’s “The Old Man and the Sea” and visualizes the iceberg theory to understand them by utilizing network analysis. Network analysis enables multidimensional examination of the author’s emotions and values by considering the correlation between language expressions reflecting the author’s consciousness. First, the analysis showed the changes in the positive and negative aspects of emotion words according to the narrative structure by analyzing the frequency of emotion words and the frequency of emotion words that co-occur with the topic words. Second, UCINET was used to extract centrality, clustering, and network strength indicators, and the correlation between topic words and emotion words was quantified and visualized based on them. By tracking the changes in emotion words and their connections at each stage, it was possible to clearly confirm what emotions the author emphasized in what situations and how they influenced the overall story. Through specific numerical indicators provided by various indicators of the network, this study objectively quantified the correlation between topic words and emotion words, such as which emotion words are connected to the topic words and the strength of the connection. This quantitative linguistic and network analysis objectively proves how the author’s intention and message are reflected in language, and it also enabled observations of aspects that are difficult to perceive intuitively, highlighting the importance of these research methodologies in language studies.
Abstract
This study analyzes the meaning and emotions conveyed in Hemingway’s “The Old Man and the Sea” and visualizes the iceberg theory to understand them by utilizing network analysis. Network analysis enables multidimensional examination of the author’s emotions and values by considering the correlation between language expressions reflecting the author’s consciousness. First, the analysis showed the changes in the positive and negative aspects of emotion words according to the narrative structure by analyzing the frequency of emotion words and the frequency of emotion words that co-occur with the topic words. Second, UCINET was used to extract centrality, clustering, and network strength indicators, and the correlation between topic words and emotion words was quantified and visualized based on them. By tracking the changes in emotion words and their connections at each stage, it was possible to clearly confirm what emotions the author emphasized in what situations and how they influenced the overall story. Through specific numerical indicators provided by various indicators of the network, this study objectively quantified the correlation between topic words and emotion words, such as which emotion words are connected to the topic words and the strength of the connection. This quantitative linguistic and network analysis objectively proves how the author’s intention and message are reflected in language, and it also enabled observations of aspects that are difficult to perceive intuitively, highlighting the importance of these research methodologies in language studies.
참고문헌 (20)
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