• Journal of Intelligence and Information Systems
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• v.28 no.3
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• pp.161-183
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• 2022

Opinion polls have become a powerful means for election campaigns and one of the most important subjects in the media in that they predict the actual election results and influence people's voting behavior. However, the more active the polls, the more often they fail to properly reflect the voters' minds in measuring the effectiveness of election campaigns, such as repeatedly conducting polls on the likelihood of winning or support rather than verifying the pledges and policies of candidates. Even if the poor predictions of the election results of the polls have undermined the authority of the press, people cannot easily let go of their interest in polls because there is no clear alternative to answer the instinctive question of which candidate will ultimately win. In this regard, we attempt to retrospectively grasp public opinion on the 20th presidential election by applying the 'YouTube Analysis' function of Sometrend, which provides an environment for discovering insights through online big data. Through this study, it is confirmed that a result close to the actual public opinion (or opinion poll results) can be easily derived with simple YouTube data results, and a high-performance public opinion prediction model can be built.

• Journal of the Korea Convergence Society
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• v.13 no.4
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• pp.359-372
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• 2022

This study aimed to derive a YouTube content strategy that can be exposed to Trending for a long time by comparing the features of 20 channels in the short/long term using 'YouTube Trending' data in 2021. First, through Pearson's correlation analysis, we found that various factors such as 'the number of title or tag letters' related to long-term exposure, and set this as an index to compare features. As a result, 1)'video title' of about 40-45 letters without excessive special characters, 2)'video length' within 10 minutes, 3)'Video description' is effective when writing 2-3 sentences and adding SNS information or including 3 key tags. Also, it would be more effective if you set key tag pairs such as (먹방, mukbang), (역대급, 레전드) derived through text mining. Through this, the channel will spread globally, bringing various advantages, and will be used as an indicator to evaluate the globality of the channel.

• Journal of the Korean Society for Library and Information Science
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• v.56 no.4
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• pp.515-536
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• 2022

The purpose of this study is to understand the content characteristics in YouTube videos of the National Archives of Korea. For this purpose, keywords, video data, and viewer responses were collected for 324 videos posted by the National Archives of Korea for five years since April, 2017. Social network analysis, topic modeling, and content analysis were performed. Based on this, the main keywords leading the YouTube videos of the National Archives of Korea, 7 major topics and 20 sub-topics were identified. The characteristics of the YouTube videos and keywords network were studies. In addition, video characteristics were analyzed as external characteristics, video editing and delivery methods, and content characters. The study found that the YouTube channel of the National Archives of Korea has been posting the videos related to various topics such as places, history, and events as well as the basic functions of the archives to induce viewers' interest in the archives. The study also identified the areas that needed to be improved such as low response from viewers, lack of content that could interest viewers, and lack of channel operation to interact or communicate with viewers. Finally, the study was concluded with a proposal to spread the videos of the National Archives of Korea to more users.

• Journal of Intelligence and Information Systems
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• v.28 no.1
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• pp.1-28
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• 2022

In recent years, many Internet giants have begun providing their own content services, which attract online users by offering personalized services based on artificial intelligence technologies. This study investigates the role of two firms' content services within the firms' online service network. We examine the role of Naver Webtoon, which can be characterized as a professional-generated content, within Naver's service portfolio, and that of Google YouTube, which can be characterized as a user-generated content, within Google's service portfolio. Using survey data on viewers' use of the two services, we analyze a valued directed service network, where a node denotes an online service and a relationship between two nodes denotes a sequential use of two services. We found that both Webtoon and YouTube show higher out-degree centrality than in-degree centrality, which implies these content services are more likely to be starting services rather than arriving services within the firms' interactive network. The gap between the out-degree and in-degree centrality of YouTube is much smaller than that of Webtoon. The high centrality of YouTube, a user-generated content service, within the Google service network shows that YouTube's initial role of providing specific-content videos (e.g., entertainment) has expanded into a general search service for users.

• The Journal of the Korea Contents Association
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• v.22 no.8
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• pp.106-114
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• 2022

This study attempted to empirically investigate the difference in the Advertising Acceptance Attitudes of pre-roll advertisements according to the Use Motivation and Use Intensity of YouTube, which act as important factors in using YouTube. For this study, a survey targeted to both male and female university students was conducted, 200 people's data being used for the analysis. First research result was that positive attitude towards advertisement based on the Youtube Use Motivation was higher for the group who pursue narrative identities than the group who habitually use intention and pursue amusement. For avoidance behavior, the group who habitually use intention and pursue amusement was higher than the group who pursue narrative identities. Second, for the positive attitude towards advertisement based on Youtube Use Intensity, the group with higher Use Intensity showed an optimistic attitude relative to the group with lower Use Intensity. However, there was no difference in the avoidance behavior for advertisement. These following results imply that a strategy considering the Use Pattern based on the Use Motivation and Use Intensity of the users is needed in enforcing YouTube pre-roll advertisements.

• Journal of Intelligence and Information Systems
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• v.29 no.4
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• pp.1-13
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• 2023

The widespread adoption of smartphones and advancements in internet technology have notably shifted content consumption habits toward video. This research aims to dissect the nature of videos posted on YouTube, the global video-sharing platform, to understand the characteristics of both produced and preferred content. For this study, dance was chosen as a specific subject from a variety of video categories. Data on YouTube videos associated with the term "dance" was compiled over three years, from 2019 to 2021. The investigation revealed a clear distinction between the types of dance videos frequently uploaded to YouTube and those that receive a high number of views. The empirical analysis of this study indicates a viewer preference for vlogs that provide insights into the daily lives of dance students, as well as for purpose-driven videos, such as those highlighting dance exam preparations or school dance events. Notably, the vlogs that attract the most attention are typically created by dance students at the college or secondary school level, rather than by professionals. Although the study was focused on dance, its methodologies can be applied to different subjects. These insights are expected to contribute to the development of a recommendation system that aids content creators in effectively targeting their productions.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.18 no.2
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• pp.420-437
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• 2024

There are some problems in network traffic classification (NTC), such as complicated statistical features and insufficient training samples, which may cause poor classification effect. A NTC architecture based on one-dimensional Convolutional Neural Network (CNN) and transfer learning is proposed to tackle these problems and improve the fine-grained classification performance. The key points of the proposed architecture include: (1) Model classification--by extracting normalized rate feature set from original data, plus existing statistical features to optimize the CNN NTC model. (2) To apply transfer learning in the classification to improve NTC performance. We collect two typical network flows data from Youku and YouTube, and verify the proposed method through extensive experiments. The results show that compared with existing methods, our method could improve the classification accuracy by around 3-5%for Youku, and by about 7 to 27% for YouTube.

• Fourth Industrial Review
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• v.4 no.1
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• pp.29-36
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• 2024

Purpose: This study is a prior study for expanding the science museum's online services. Based on case studies, we propose an online service for science museums in the future. Research design, data, and methodology: This study analyzed online-based science museums services trends. The data was collected based on the cases of five national science museums. To understand the characteristics of science museum's online services, we analyzed the status of digital content provided by each science museum and the operation method of online special exhibitions. Result: The national science museums provided online services through virtual science museums, SNS, and YouTube. However, the services still imposed limitation on facilitating active learning for visitors. In the case of SNS and YouTube, it is only a one-time promotional tool. Conclusion: This study suggests the need for concrete measures to utilize the abundant content accumulated so far in actual education. Additionally, it emphasizes the importance of content development incorporating new platforms.

• The Journal of Information Systems
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• v.29 no.1
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• pp.267-287
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• 2020

Purpose Online platform companies can increase the spread of content by communicating with users who have diverse preferences through social networks. Previous studies show the mixed effect on the network overlap, and there was a limited examinations for the underlying mechanism. This study expects high academic and practical implications that can be provided by studying on the user's viewership network. The purpose of this research is to examine the effects of network overlap on the users' viewership for creators of user-generated content in YouTube. We explain the direct and in-direct effects through the content sharing and the valence of user ratings. Design/methodology/approach The data contains 45 channels and 4,085 video clips from YouTube. We control the effect of the categories, channel characteristics, and vide clip characteristics on the viewership. PROCESS macro were used to analyze the direct and in-direct effects of network overlap. Findings The analysis results showed that the network overlap directly affect on the users' viewership. The variable decreases the moderators (i.e., content sharing and the valence of user ratings). This result implies that the users can not satisfy their need for uniqueness which is achieved by content sharing and rating in the overlapped network.

• International Journal of Internet, Broadcasting and Communication
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• v.11 no.3
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• pp.95-105
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• 2019

A great deal needs to be learned about why and how users participate and consume information on various online sites. The design of socio-technical systems especially for promoting engagement in terms of maximum user participation is both a theoretical and real-world challenge that researchers strive to understand. At present, most of the research on the motives of Internet video users' behavior focuses on the user's "viewing motivation" and "sharing motivation", and lacks the analysis of the factors affecting users' "subscription motivation". This study will attempt to compensate for this gap. Based on the YouTube platform, we take Chinese video users as the research object and uses the "Censydiam user motivation analysis model" to make assumptions about user subscription motivation from the two levels of social needs and personal needs, using regression analysis. Validate the hypothesis and get the influencing factors that may be available in the user's subscription motivation based on the assumptions. Built on survey data from 215 respondents, the study found that Enjoyment, Vitality, Power, and Conviviality are four factors that influence user motivation.