• The Research Journal of the Costume Culture
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• v.29 no.2
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• pp.289-306
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• 2021

The study aims to define the Korean Wave as global attention to Korea's unique culture and consider the specificity of traditional Korean fashion images in Korean Wave content. The research method of this study is a case study through literature research. In order to collect Korean Wave content on YouTube, 24 channels with the highest number of views were selected from among content uploaded from 2018 to the present through keyword search, and up to two channels with high views showing traditional Korean fashion images. As a result of selecting the analysis target, 41 Korean Wave videos and 368 costumes were selected and analyzed based on fashion style elements, including item, color, detail, motif, styling, silhouette, and accessory. As a result of the study, music, broadcast, fashion, and other content were found in the Korean Wave content fields in which Korean fashion style appeared, and the characteristics of each field were derived. Music content was characterized by fashion style excluding stereotypes about traditional Korean costume, broadcast and fashion content was characterized by fashion style inherited from traditional costume, and other content was characterized by symbolic fashion style of traditional culture. This study is meaningful in revealing the formative characteristics of traditional Korean design elements recently shared online through the study of Korean traditional fashion images in Korean Wave content.

• International Journal of Internet, Broadcasting and Communication
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• v.14 no.2
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• pp.63-69
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• 2022

We develop a smart tourism information system that provides smart tourism services to free independent tourists (FITs) through various content distribution channels such as mobile apps, Instagram, YouTube, and chatbots. The smart tourism information system provides location and storytelling-based tourism information, accommodation, restaurant information, and recommended travel products so that tourists can create a travel itinerary based on personalized situation awareness. The smart tourism information system also provides smart tourism services using commercial maps, navigation, and weather forecast APIs from the Korea Meteorological Administration to provide smart tour guide services to tourists who travel according to the travel itinerary. In this paper, we develop the React Native app that provides smart tourism services provided by the smart tourism information system. The smart tourism React Native app has implemented two methods: a method that directly connects to the smart tourism information system, and a method that provides services by interworking through the GraphQL Query Language developed by META (Facebook). The smart tourism React Native app implements OSMU (One Source Multi-use) by providing tourism information from mobile apps, photos from Instagram, and drone videos from YouTube as an integrated UI.

• The Journal of Information Systems
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• v.32 no.2
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• pp.177-190
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• 2023

Purpose Recently, as a new business marketing tool, short form content focused on fun and interest has been shared as hashtags. By extracting positive and negative keywords from media audiences through comment analysis of social media news, various stakeholders aim to quickly and easily grasp users' opinions on major news. Design/methodology/approach YouTube videos were searched using the YouTube Data API and the results were collected. Video comments were crawled and implemented as HTML elements, and the collection results were checked on the web page. The collected data consisted of video thumbnails, titles, contents, and comments. Comments were word tokenized with the R program, comparing positive and negative dictionaries, and then quantifying polarity. In addition, social network analysis was conducted using divided positive and negative comments, and the results of centrality analysis and visualization were confirmed. Findings Social media users' opinions on issue news were confirmed by analyzing and visualizing the centrality of keywords through social network analysis by dividing comments into positive and negative. As a result of the analysis, it was found that negative objective reviews had the highest effect on information usefulness. In this way, previous studies have been reaffirmed that online negative information has a strong effect on personal decision-making. Corporate marketers will analyze user comments on social network services (SNS) to detect negative opinions about products or corporate images, which will serve as an opportunity to satisfy customers' needs.

• The Journal of the Korea Contents Association
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• v.21 no.11
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• pp.112-120
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• 2021

Korea and Japan share the same view of a single nation state, but there was a difference in the government's COVID-19 emergency relief fund for foreigners. To this end, I analyzed the comments of Korean and Japanese users in YouTube videos related to COVID-19 disaster support funds for foreigners. As a result of the study, As a result, there are many opinions that Korea and Japan are generally sensitive to foreigners' tax payments, and that immigrants can receive national benefits and support like indigenous people if they fulfill their obligations. Next, it can be seen that Korea and Japan recognize each other in common. The difference is that Japan is sensitive to the same nationality, whereas Korea is more focused on tax and money than nationality.

• The Journal of the Korea Contents Association
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• v.22 no.4
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• pp.261-272
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• 2022

This study investigated the relationship between selective exposure, attitude polarization, and online political participation among 420 YouTube political video users. Additionally, the mediating effect of attitude polarization on the relationship between selective exposure and online political participation was examined. The main results were derived by conducting exploratory factor analysis, correlation analysis, and structural model analysis using the SPSS 21.0 program and AMOS 21.0 program. The results were presented as follows. First, selective exposure had a positive effect on attitude polarization. Second, selective exposure had a positive effect on online political participation. Third, attitude polarization had a positive effect on online political participation. Fourth, attitude polarization was found to mediate the relationship between selective exposure and online political participation. In summary, it was confirmed that selective exposure to YouTube political videos increased attitude polarization and online political participation, and the more the attitude polarization was strengthened by selective exposure, the more it led to online political participation.

• The Journal of the Korea Contents Association
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• v.22 no.4
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• pp.479-487
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• 2022

This study divided video content of current representative YouTube channels on Chinese language education into internal and external elements for analysis. By examining these channels, this study found that they have various external and internal elements. In addition, YouTube classes also have certain distinct characteristics that are non-existent in traditional classroom or face-to-face classes, and show potential to serve as a new educational medium that can fill the gaps in existing classroom classes. However, a large number of these channels still have problems with their internal and external elements, which seem to require not only the effort and attention of the instructors creating the videos, but also considerable time and human and material resources.

• The Journal of the Convergence on Culture Technology
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• v.9 no.1
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• pp.595-603
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• 2023

Recently, many public institutions have been conducting promotional activities using digital platforms. Communication methods using digital platforms have a very important meaning in that they can create new values that did not exist before by connecting and sharing information with various users. To this end, we tried to analyze YouTube videos of five government ministries and examine them. As a result of YouTube analysis by government ministries, most of them were mainly used as channels for policy promotion, and many were used as channels for new information. Although the message is delivered through the production of various contents, it was possible to look at cases where the target as a channel for communication was not clear and the purpose was unclear. In order to communicate with the people, it should be used as a channel for communication through content suitable for clear target setting and purpose.

• Journal of Information Technology Services
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• v.23 no.3
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• pp.103-118
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• 2024

Due to the advancement of virtual reality technology, virtual idols are widely used in industrial and cultural content industries. However, it is difficult to utilize virtual idols' social perceptions because they are not properly understood. Therefore, this paper collected and analyzed YouTube comments to identify differences about social perception through comparative analysis between virtual idols and general idols. The dataset was constructed by crawling comments from music videos with more than 10 million views of virtual idols and more than 10,000 comments. Keyword frequency and TF-IDF values were derived from the collected dataset, and the connection centrality CONCOR cluster was analyzed with a semantic network using the UCINET program. As a result of the analysis, it was found that virtual idols frequently used keywords such as "person," "quality," "character," "reality," "animation," while reactions and perceptions were derived from general idols. Based on the results of this analysis, it was found that while general idols are mainly evaluated with their appearance and cultural factors, social perceptions of virtual idols' values are mixed with evaluations of cultural factors such as "song," "voice," and "choreography," focusing on technical factors such as "people," "quality," "character," and "animation." However, keywords such as "song," "voice," "choreography," and "music" are included in the top 30 like regular idols and appear in the same cluster, suggesting that virtual idols are gradually shifting away from minority tastes to mainstream culture. This study aims to provide academic and practical implications for the future expansion of the industry and cultural content industry of virtual idols by grasping the social perception of virtual idols.

• Journal of Korea Society of Industrial Information Systems
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• v.29 no.1
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• pp.91-105
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• 2024

Car accidents occur as a result of collisions between vehicles, leading to both vehicle damage and personal and material losses. This study developed a vehicle accident detection model based on 2,550 image frames extracted from car accident videos uploaded to YouTube, captured by CCTV. To preprocess the data, bounding boxes were annotated using roboflow.com, and the dataset was augmented by flipping images at various angles. The You Only Look Once version 8 (YOLOv8) model was employed for training, achieving an average accuracy of 0.954 in accident detection. The proposed model holds practical significance by facilitating prompt alarm transmission in emergency situations. Furthermore, it contributes to the research on developing an effective and efficient mechanism for vehicle accident detection, which can be utilized on devices like smartphones. Future research aims to refine the detection capabilities by integrating additional data including sound.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.10a
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• pp.189-192
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• 2021

YouTube, the world's largest video sharing platform, is loved by many users in that it provides numerous videos and makes it easy to get helpful information. However, the ratio of like/hate for each video varies according to the subject or upload time, even though they are in the same channel; thus, previous studies try to understand the reason by inspecting some numerical statistics such as the ratio and view count. They can help know how each video is preferred, but there is an explicit limitation to identifying the cause of such preference. Therefore, this study aims to determine the reason that affects the preference through matching between topic words extracted from comments in each video and non-sympathetic types defined in advance. Among the top 10 channels in the field of 'pets' and 'cooking', where outliers occur a lot, the top 10 videos (the threshold of pet: 4.000, the threshold of cooking: 0.723) with the highest ratio were selected. 11,110 comments collected totally, and topics were extracted and matched with non-sympathetic types. The experimental results confirmed that it is possible to predict whether the rate of like/hate would be high or which non-sympathetic type would be by analyzing the comments.