• The Journal of the Korea Contents Association
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• v.20 no.6
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• pp.241-255
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• 2020

The purpose of this study is to analyze musical performances with the use of performance booking information from 2017 to 2019 which was obtained in Korea performing Arts Box Office Information system (KOPIS), and to make suggestions of Korean musical performances. Based on the data of KOPIS, relevant studies, internet based information, news articles, and magazines, musical performances were analyzed. In addition, the previous data of KOPIS and the data of the Broadway League were analyzed. The analysis results are as follows. Firstly, it is necessary to concentrate on Korean mid-sized theatre musical performances. Secondly, producers need to open their production costs invested in performances transparently. Thirdly, Off-Broadway system needs to be introduced after being modified in consideration of Korean situations. Thirdly, it is necessary to make long-run performances in order to achieve commercial success. Fifthly, it is necessary to make a bold attempt of theatre for performances just as in Broadway.

• The Journal of Society for e-Business Studies
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• v.26 no.2
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• pp.19-43
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• 2021

The prediction of box office performance in performing arts institutions is an important issue in the performing arts industry and institutions. For this, traditional prediction methodology and data mining methodology using standardized data such as cast members, performance venues, and ticket prices have been proposed. However, although it is evident that audiences tend to seek out their intentions by the performance guide poster, few attempts were made to predict box office performance by analyzing poster images. Hence, the purpose of this study is to propose a deep learning application method that can predict box office success through performance-related poster images. Prediction was performed using deep learning algorithms such as Pure CNN, VGG-16, Inception-v3, and ResNet50 using poster images published on the KOPIS as learning data set. In addition, an ensemble with traditional regression analysis methodology was also attempted. As a result, it showed high discrimination performance exceeding 85% of box office prediction accuracy. This study is the first attempt to predict box office success using image data in the performing arts field, and the method proposed in this study can be applied to the areas of poster-based advertisements such as institutional promotions and corporate product advertisements.

• The Journal of Bigdata
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• v.9 no.1
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• pp.197-208
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• 2024

Today, faculty performance evaluations conducted in universities to comprehensively assess faculty members have yielded outcomes that deviate from the original intent of the system due to its quantitative assessment-centric approach. The field of theater arts, in particular, faces challenges in fairly and objectively measuring research and creative achievements through traditional quantitative evaluation methods, owing to the highly subjective nature of its outputs compared to other academic disciplines. This study proposes a method to improve the evaluation of research and creative achievements in the field of theater arts through the utilization of big data. First, we investigated the current evaluation criteria and methods used in research and creative achievement assessments in theater arts departments at major domestic universities. Next, we analyzed the key issues related to the existing evaluation system for research and creative achievements in the field of theater arts. Finally, we presented an improvement plan for the evaluation system using the big data available from the Korea Performing Arts Box Office Information System (KOPIS). This study aims to support the research and creative activities of theater arts faculty more effectively and to enhance the competitive edge of universities.

• The Journal of the Korea Contents Association
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• v.21 no.9
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• pp.372-390
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• 2021

The objective of this study is to understand the current status of damage to Korean musical caused by the COVID-19, and also to seek for the coping measures and development direction in the post-Corona era. Thus, to understand the current status of damage, this study mainly researched the contents of NAVER TV musical performance transmitted for three years from March 2018 to February 2021 for analyzing the online performance and performance statistical data of Performing Arts Box Office Information System. As a result, this study could find a hypothesis and grounds to simultaneously verify and draw the positive and negative sides, pessimistic implications, and optimistic possibility. First, the performing arts would be multilaterally expanded after being divided into offline performance and online performance. Second, the utilization of online performance could narrow the gap(polarization) between capital area and non-capital area. Third, it is urgently needed to develop a win-win model for the establishment of a new musical market. Fourth, the performers' copyrights should be fairly protected. Fifth, the visualization requires the Korean-style support foundation and talent equipped with convergent thinking and knowledge. In such temporal changes from offline performance to online performance, there should be more sophisticated qualitative and quantitative growth in musical market.