• Industry Promotion Research
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• v.9 no.3
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• pp.193-203
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• 2024

This study analyzes user behavior on YouTube Shorts within snack culture and proposes short-form video production strategies by identifying key value factors. Prior research identified seven characteristics (playfulness, time killing, information provision, social presence, interactivity, escapism, conciseness) and criteria based on the 5W1H principles. Surveys and interviews revealed that key user values are playfulness, time killing, conciseness, and interactivity. Users engage without specific purposes, watch 10-20 consecutive pieces selectively, and use it in comfortable environments. This research provides insights for understanding user behavior and short-form video production strategies.

• Proceedings of the Korea Information Processing Society Conference
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• 2023.11a
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• pp.667-668
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• 2023

IT 기술의 발달로 인해 뉴스를 제공하는 플랫폼들이 다양해 졌고 최근 해외 인터뷰 영상, 해외 뉴스를 Youtube Shorts형태로 제작하여 화자의 의도와는 다른 자막을 달며 가짜 뉴스가 생성되는 문제가 대두되고 있다. 이에 본 논문에서는 Sentence-BERT를 활용한 YouTube 가짜 뉴스 탐지 시스템을 제안한다. 제안하는 시스템은 Python 라이브러리를 사용해 유튜브 영상에서 음성과 영상 데이터를 분류하고 분류된 영상 데이터는 EasyOCR을 사용해 자막 데이터를 텍스트로 추출 후 Sentence-BERT를 활용해 문자 유사도를 분석한다. 분석결과 음성 데이터와 영상 자막 데이터가 일치한 경우 일치하지 않은 경우보다 약 62% 더 높은 문장 유사도를 보였다.

• The Journal of the Convergence on Culture Technology
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• v.7 no.4
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• pp.659-665
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• 2021

Short video applications (e.g., TikTok, YouTube shorts) are growing quickly in terms of active users and usage time. Of course, advertising industry is utilizing the app as AD channel. The current study, however, argues that the effectiveness of ADs in short video apps are not articulated well and that precise research for measuring the effect is required. In this context, this study measured the effects of storytelling ad types(reality, parody, creative) and message sensation value(high vs. low level) on story transportation. The notable finding is that when creative storytelling ad type which requires more cognitive resources than other two types meets high level of message sensation value, ad viewers could reach cognitive overload state which induced low effectiveness of ad. As its result, the effectiveness of AD reduced. More specific theoretical discussion and suggestions for advertising producers are described.

• Journal of Platform Technology
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• v.12 no.1
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• pp.55-66
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• 2024

The K-POP market has become influential not only in culture but also in society as a whole, including diplomacy and environmental movements. As a result, various papers have been conducted based on machine learning to identify the success factors of idols by utilizing traditional data such as music and recordings. However, there is a limitation that previous studies have not reflected the influence of new media platforms such as Instagram releases, YouTube shorts, TikTok, Twitter, etc. on the popularity of idols. Therefore, it is difficult to clarify the causal relationship of recent idol success factors because the existing studies do not consider the daily changing media trends. To solve these problems, this paper proposes a data collection system and analysis methodology for idol-related data. By developing a container-based real-time data collection automation system that reflects the specificity of idol data, we secure the stability and scalability of idol data collection and compare and analyze the clusters of successful idols through a K-Means clustering-based outlier detection model. As a result, we were able to identify commonalities among successful idols such as gender, time of success after album release, and association with new media. Through this, it is expected that we can finally plan optimal comeback promotions for each idol, album type, and comeback period to improve the chances of idol success.