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This study aims to observe the contexts in which domestic researchers select and utilize the concepts of ‘artistic labor’ and ‘creative labor’—which provide major theoretical foundations in academic discussions on ‘artists’—to examine how the domains of ‘artists’ and ‘cultural industry workers’ relate to the policy-driven concept of ‘artist.’ The research collected KCI-listed and candidate papers related to artists published between 2009 and 2023, categorizing those that included ‘artistic labor’ and ‘creative labor’ as primary keywords. Using the open-source software R, abstracts were gathered and preprocessed. Subsequently, word frequency analysis, topic modeling, and semantic network analysis were conducted. The results revealed that discussions on artistic labor predominantly focused on areas of traditional artists, emphasizing social contributions, regional interactions, and cultural value. In contrast, discussions on creative labor were more closely linked to cultural industry workers, centering on commercial aims such as technological innovation, digital transformation, and industrial outcomes. Notably, given the prevailing confusion between the legal status of ‘artists’ and the traditional concept of ‘artist’ itself, the f indings indicate that domestic researchers rarely utilize the concept of ‘artist’ when studying the labor of cultural industry workers. These findings suggest a need for differentiated policy approaches that reflect the unique characteristics and labor dynamics of both artists and cultural industry workers. Furthermore, for domestic research on artists to expand into international academic discussions, the study highlights the necessity of distinguishing between artists and cultural industry workers and incorporating policies that align with international standards, thereby justifying national support tailored to each group.
키워드
- 제목
- 예술노동과 창의노동의 개념적 경계에 대한 탐색적 연구- LDA 토픽모델링과 의미연결망 분석을 중심으로 -
- 제목 (타언어)
- Conceptual Boundaries between Artistic Labor and Creative Labor: Focusing on LDA Topic Modeling and Semantic Network Analysis
- 저자
- 안채린
- 발행일
- 2024-11
- 저널명
- 예술경영연구
- 호
- 72
- 페이지
- 217 ~ 252