On the improvement, innovation and inheritance of stage makeup styling in opera under the background of big data
Character styling design can clearly show the background of story characters and the characteristics of the times in the performance of stage plays. Integrating traditional culture with the art of stage plays is important for developing theatrical communication. In this paper, we analyze the factors...
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| Format: | Article |
| Language: | English |
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Sciendo
2024-01-01
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| Series: | Applied Mathematics and Nonlinear Sciences |
| Subjects: | |
| Online Access: | https://doi.org/10.2478/amns.2023.1.00066 |
| _version_ | 1797340906138894336 |
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| author | Zhao Yuqi |
| author_facet | Zhao Yuqi |
| author_sort | Zhao Yuqi |
| collection | DOAJ |
| description | Character styling design can clearly show the background of story characters and the characteristics of the times in the performance of stage plays. Integrating traditional culture with the art of stage plays is important for developing theatrical communication. In this paper, we analyze the factors that impact theatrical communication in the context of big data. Based on the original innovation diffusion model, it analyzes the limitations of its application, analyzes the innovation characteristics of theatrical stage makeup modeling from a qualitative perspective, finds that its diffusion characteristics do not conform to the prerequisite assumptions of the original innovation diffusion model, and confirms the improvement direction of the innovation diffusion model. Based on the analysis of audience data by the full data analysis method, the main influencing factors affecting the diffusion of opera heritage are identified, and their practical significance in the improved model is analyzed. The original innovation diffusion model is improved quantitatively, and an iterative diffusion model is established. Empirical analysis of the iterative diffusion model was conducted using the actual diffusion data of opera stage makeup styling. The research results show that the initial diffusion rates of the products are, in descending order, Cheese Superman, TikTok, Watermelon Video, and Punchbowl. Among them, the cumulative diffusion of TikTok is the highest at 14, and the diffusion rate of Watermelon Video is 0.68. It indicates that the above products effectively spread opera culture and highlight the charm of opera stage makeup styling. |
| first_indexed | 2024-03-08T10:10:10Z |
| format | Article |
| id | doaj.art-d99ea42acfd544de8c1a93e8f105ee46 |
| institution | Directory Open Access Journal |
| issn | 2444-8656 |
| language | English |
| last_indexed | 2024-03-08T10:10:10Z |
| publishDate | 2024-01-01 |
| publisher | Sciendo |
| record_format | Article |
| series | Applied Mathematics and Nonlinear Sciences |
| spelling | doaj.art-d99ea42acfd544de8c1a93e8f105ee462024-01-29T08:52:25ZengSciendoApplied Mathematics and Nonlinear Sciences2444-86562024-01-019110.2478/amns.2023.1.00066On the improvement, innovation and inheritance of stage makeup styling in opera under the background of big dataZhao Yuqi01Academy of music, Introduction of Henan University, Kaifeng, Henan, 475000, ChinaCharacter styling design can clearly show the background of story characters and the characteristics of the times in the performance of stage plays. Integrating traditional culture with the art of stage plays is important for developing theatrical communication. In this paper, we analyze the factors that impact theatrical communication in the context of big data. Based on the original innovation diffusion model, it analyzes the limitations of its application, analyzes the innovation characteristics of theatrical stage makeup modeling from a qualitative perspective, finds that its diffusion characteristics do not conform to the prerequisite assumptions of the original innovation diffusion model, and confirms the improvement direction of the innovation diffusion model. Based on the analysis of audience data by the full data analysis method, the main influencing factors affecting the diffusion of opera heritage are identified, and their practical significance in the improved model is analyzed. The original innovation diffusion model is improved quantitatively, and an iterative diffusion model is established. Empirical analysis of the iterative diffusion model was conducted using the actual diffusion data of opera stage makeup styling. The research results show that the initial diffusion rates of the products are, in descending order, Cheese Superman, TikTok, Watermelon Video, and Punchbowl. Among them, the cumulative diffusion of TikTok is the highest at 14, and the diffusion rate of Watermelon Video is 0.68. It indicates that the above products effectively spread opera culture and highlight the charm of opera stage makeup styling.https://doi.org/10.2478/amns.2023.1.00066big data backgroundon opera stagemakeup modelinginnovation diffusion modeliterative diffusion model62-07 |
| spellingShingle | Zhao Yuqi On the improvement, innovation and inheritance of stage makeup styling in opera under the background of big data Applied Mathematics and Nonlinear Sciences big data background on opera stage makeup modeling innovation diffusion model iterative diffusion model 62-07 |
| title | On the improvement, innovation and inheritance of stage makeup styling in opera under the background of big data |
| title_full | On the improvement, innovation and inheritance of stage makeup styling in opera under the background of big data |
| title_fullStr | On the improvement, innovation and inheritance of stage makeup styling in opera under the background of big data |
| title_full_unstemmed | On the improvement, innovation and inheritance of stage makeup styling in opera under the background of big data |
| title_short | On the improvement, innovation and inheritance of stage makeup styling in opera under the background of big data |
| title_sort | on the improvement innovation and inheritance of stage makeup styling in opera under the background of big data |
| topic | big data background on opera stage makeup modeling innovation diffusion model iterative diffusion model 62-07 |
| url | https://doi.org/10.2478/amns.2023.1.00066 |
| work_keys_str_mv | AT zhaoyuqi ontheimprovementinnovationandinheritanceofstagemakeupstylinginoperaunderthebackgroundofbigdata |