Serial Number:  http://www.riss.kr/link?id=A106238958

Title:  An Analysis of Arts Management-Related Studies’ Trend in Korea using Topic Modeling and Semantic Network Analysis

Author: Hwang, seol & Park, Yang-woo

Journal: Korean association of arts management

Vol: Vol.0 No.50

Pages: 5-31(27)

Published by: Korean Association Of Arts Management

Date: 2019. 

Register Information: KCI

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<Abstract>

The main purpose of this study was to use Deep Learning based Topic Modeling and Semantic Network Analysis to examine research trend of arts management-related papers in korea. For this purpose, research subjects such as ‘The Journal of Cultural Policy’, ‘The Journal of Cultural Economics’, ‘The Journal of Culture Industry’, ‘The Journal of Arts Management’, and ‘The Journal of Human Content’, which are the registered journal of the National Research Foundation of Korea directly or indirectly related to arts management field.
From 1988 to 2017, a total of 2,110 domestic journals' signature, abstract, and keyword were analyzed. We tried Big Data analysis such as Topic Modeling and Semantic Network Analysis to examine changes in trends in arts management.
The analysis program used open software R and standard statistical software SPSS. Based on the results of the analysis, the implications and limitations of the study and suggestions for future research were discussed. And the potential for development of convergent research such as Arts & Artificial Intelligence and Arts & Big Data.