• Journal of Fashion Business
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• v.28 no.3
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• pp.16-33
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• 2024

This study investigated the role of YouTube in providing fashion information and explored how fashion companies and individual YouTubers used this platform to communicate with consumers and disseminate fashion contents. This research identified two main types of YouTube information providers: fashion companies and fashion YouTubers. It focused on characteristics of YouTube fashion information (such as informativity, novelty, usefulness, authenticity, and enjoyment) and their impact on consumer needs satisfaction, information satisfaction, and information acceptance. An online survey was conducted with female consumers aged 20 to 39 years, analyzing responses to assess how YouTube fashion information affected consumer behavior and decision-making. Using SPSS for statistical analysis, results indicated that usefulness and enjoyment significantly influenced information acceptance, particularly with fashion companies showing a stronger impact from usefulness, while authenticity and enjoyment were more influential for fashion YouTubers. Moreover, mediating effects of consumer needs satisfaction and information satisfaction on the relationship between fashion information characteristics and information acceptance were examined. Findings revealed that various characteristics had different mediating effects based on whether the information provider was a fashion company or a fashion YouTuber. Notably, enjoyment and authenticity played crucial roles in mediating consumer needs satisfaction. Overall, this study provides insights into how YouTube serves as a vital channel for fashion information, influencing consumer satisfaction and behavior. It also offers practical implications for fashion marketers on how to leverage YouTube effectively to meet consumer needs and enhance information acceptance, thereby proposing strategic marketing recommendations for fashion companies and YouTubers.

• The Journal of the Korea Contents Association
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• v.21 no.10
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• pp.127-137
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• 2021

YouTube beauty content channels that utilize various topics and formats are undergoing quantitative and qualitative expansion. This study selected the top five channels represeting major domestic and foreign beauty brands, fashion magazines and beauty influencers through Statista and conducted a case study focusing on them. It will connect to a strategy for increasing beauty-related content by comparing content characteristics according to content producers. Also, it will help to reveal what types of content will be appealing more attractive to consumer. The result has shown that the growth of YouTube platforms has transformed passive consumers into new communicators by diversifying sources of product information. In addition, as content of different type was consumed by different producers, producer-oriented content was produced rather than objective journalistic gaze. Therefore, it was found that the delivery of 'brand values' that can strengthen the relationship between consumers and brands along with various entertainment elements that are effective for millennial in the future.

• Journal of the Korea Society of Computer and Information
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• v.27 no.12
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• pp.111-119
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• 2022

The purpose of this paper is to examine the change in perception of 3D virtual fashion before and after COVID-19 using big data analysis. The data collection period is from January 1, 2017, before the outbreak of COVID-19, to October 30, 2022, after the outbreak. Big data was collected for key words related to 3D virtual fashion extracted from social media such as Naver, Daum, Google, and YouTube using Textom. After the collected words were refined, word cloud, word frequency, connection centrality, network visualization, and CONCOR analysis were performed. As a result of extracting and analyzing 32,461 words with 3D virtual fashion as a keyword, the frequency and centrality of fashion, virtual, and technology appeared the highest, and the frequency of appearance of digital, design, clothing, utilization, and manufacturing was also high. Through this, it was found that 3D virtual fashion is being used throughout the industry along with the development of technology. In particular, the key words that stand out the most after COVID-19 are metaverse and 3D education, which are in high demand in the fashion industry.

• Journal of Intelligence and Information Systems
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• v.28 no.4
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• pp.329-346
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• 2022

Recently, as the market for short form videos (Instagram, TikTok, YouTube) on social media has gradually increased, research using them is actively being conducted in the artificial intelligence field. A representative research field is Video to Shop, which detects fashion products in videos and searches for product images. In such a video-based artificial intelligence model, product features are extracted using convolution operations. However, due to the limitation of computational resources, extracting features using all the frames in the video is practically impossible. For this reason, existing studies have improved the model's performance by sampling only a part of the entire frame or developing a sampling method using the subject's characteristics. In the existing Video to Shop study, when sampling frames, some frames are randomly sampled or sampled at even intervals. However, this sampling method degrades the performance of the fashion product search model while sampling noise frames where the product does not exist. Therefore, this paper proposes a sampling method MF (Missing Fashion items on frame) sampler that removes noise frames and improves the performance of the search model. MF sampler has improved the problem of resource limitations by developing a keyframe mechanism. In addition, the performance of the search model is improved through noise frame removal using the noise detection model. As a result of the experiment, it was confirmed that the proposed method improves the model's performance and helps the model training to be effective.

• Journal of Nutrition and Health
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• v.56 no.2
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• pp.203-216
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• 2023

Purpose: This study examines the weight control behavior depending on university students' motives of using social media. Methods: The participants were 447 university students in the Jeonbuk area. Collected data were analyzed using factor analysis, cluster analysis, analysis of variance, and χ² tests with SPSS v. 26.0. Considering the motives of using social media, we investigated the usage of social media, dietary behavior related to social media, and weight control behavior. Results: Using the K-clustering method, the motives to use social media were categorized into three clusters: cluster 1 was the interest-centered group, cluster 2 was the multipurpose information-seeking group, and cluster 3 was the relationship-centered group. Among the various social media sites, YouTube (86.8%), Instagram (76.1%), and Facebook (61.1%) were the most visited by the subjects. The dietary behavior related to social media in cluster 2 was significantly higher than clusters 1 and 3 (p < 0.001). Clusters 1 and 2 showed a significantly higher dissatisfaction with one's weight (p < 0.05) and consequent interest in weight control than cluster 3 (p < 0.001). Cluster 2 used weight control-related information from social media significantly more than other clusters (p < 0.05). Weight control experiences in cluster 1 and 2 were significantly higher than in cluster 3 (p < 0.001). Conclusion: Differences in dietary behavior related to social media and weight control behavior were observed between cluster types of motivation to use social media. Based on the usage motives of university students and their behaviors, we propose that educational programs should be conducted for weight control using social media.