빅데이터 기술을 활용한 인문콘텐츠 분야의 의미연결망 분석 - 2003년부터 2015년까지 인문콘텐츠학회 논문을 중심으로 -

초록

The purpose of this study was (1) to investigate the semantic network analysis to understand the of Humanities Contents and (2) to examine the degree to which words, word clusters contributed to the formation of semantic map within the Humanities Contents. Toward this goal, we performed semantic network analysis on a total of 39 volumes of the Human Contents of Association, which were published between 2003 and 2015. The total number of papers included in the current study were 510 with 53, 983 words. The word appeared in Title analyzed the semantic network by using the R program of Big Data. The results were as follows: First, there appeared significant change in the intellectual network of Humanities Contents studies. The words and relationship networks in accordance with the periodic step was changing. There was notable paradigm shift in Humanities Contents. Second, only a few top words contributed to the formation of semantic map within the Human Contents Association studies for the past 13 years. Those words with high degree centrality included: ‘culture’, ‘contents’, ‘industry’, ‘digital’, ‘media’, ‘storytelling’. Words with betweenness centrality were very variety. As time goes by, It increased more and more. Semantic network analysis result, research in early studies was simple. To Latter increasingly complex and studies have been gradually embodied.

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