• The Journal of the Korea Contents Association
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• v.20 no.5
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• pp.513-524
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• 2020

Recently, YouTube's growth started drawing attention. YouTube is not only a content-consumption channel but also provides a space for consumers to express their intention. Consumers share their opinions on YouTube through comments. The study focuses on the text of global entrepreneurs' speeches and the comments in response to those speeches on YouTube. A content analysis was conducted for each speech and comment using the text mining software Leximancer. We analyzed the theme of each entrepreneurial speech and derived topics related to the propensity and characteristics of individual entrepreneurs. In the comments, we found the theme of money, work and need to be common regardless of the content of each speech. Talking into account the different lengths of text, we additionally performed a Prominence Index analysis. We derived time, future, better, best, change, life, business, and need as common keywords for speech contents and viewer comments. Users who watched an entrepreneur's speech on YouTube responded equally to the topics of life, time, future, customer needs, and positive change.

• Korean Medical Education Review
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• v.25 no.3
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• pp.287-288
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• 2023

• Journal of the Korea Institute of Information and Communication Engineering
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• v.23 no.11
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• pp.1321-1329
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• 2019

With the development of social information networks, the marketing methods are also changing in various ways. Unlike successful marketing methods based on existing celebrities and financial support, Influencer-based marketing is a big trend and very famous. In this paper, we first extract influencer features from more than 54 YouTube channels using the multi-dimensional qualitative analysis based on the meta information and comment data analysis of YouTube, model representative themes to maximize a personalized video satisfaction. Plus, the purpose of this study is to provide supplementary means for the successful promotion and marketing by creating and distributing videos of new items by referring to the existing Influencer features. For that we assume all comments of various videos for each channel as each document, TF-IDF (Term Frequency and Inverse Document Frequency) and LDA (Latent Dirichlet Allocation) algorithms are applied to maximize performance of the proposed scheme. Based on the performance evaluation, we proved the proposed scheme is better than other schemes.

• The Journal of the Korea Contents Association
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• v.20 no.2
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• pp.150-161
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• 2020

Generation Z(Gen Z), which is referred to people in their late teens to early 20s, becomes one of new major consumer groups in the society. More than 80 percent Gen Z use YouTube content as a main information channel. In this study, we investigate what kind of factors make Gen Z immersed when watching YouTube content. In the background study, we examined immersion and set the cognitive conditions of immersion as reality, fascination, control, and driving as a framework for analysis of case study. In the case study, we analyzed the most popular YouTube channels of each category among the Gen Z with the established framework and then identified 3 main factors: reality, 5 senses, and unpretentiousness and 8 characteristics of them. By conducting survey with Gen Z, we wanted to verify the validity of the characteristics and find out the difference among categories. Subjects answered on a five-point scale how the characteristics of each immersion factor corresponded to their favorite channels. As a result, seven characteristics: 1) familiarity of background, 2) reality of acting, 3)familiarity of material, 4)YouTubers' appearance and 5) voice, 6)multi-sensory, and 7)YouTuber's ability to resemble viewers influenced more than 50% of users' immersion. Although there was no significant difference among categories, the familiarity of the material and the five senses stimulus (YouTube's appearance, voice, audiovisual and surrogate taste) were the most important factors in the entertainment category.

• 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.

• The Journal of the Korea Contents Association
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• v.18 no.6
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• pp.50-62
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• 2018

This study is to ascertain the meaning of personal media as cultural intermediaries in the cultural diffusion, acceptance, and intermediation for the production and consumption of cultural contents. We examined the case of personal media, , which is one of popular YouTube channel in Korea and analyzed fifty most viewed videos in last two years based on four perspectives of digital cultural intermediaries: forms, expression methods, linguistic features, and evaluations. As expected, results demonstrate that shows characteristics of digital intermediary: diverse subjects without fixed rules, a variety of multimedia effects, colloquial style including neologism and multilingual, and users' high preferences caused by creator's sincerity. Our findings and limitations can serve directions of further empirical researches.

• The Journal of the Convergence on Culture Technology
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• v.8 no.2
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• pp.109-116
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• 2022

This study conducted YouTube network analysis on YouTube video related with prevention of COVID-19 and COVID-19 vaccine to explores how government's policy is spread via social media in the condition of COVID-19. As a result of network analysis on the Mask chaos, A surge in confirmed cases, supply of vaccine, the influence of media like YTN and KBS is large, their view count is high. Government highlights to inform correct information actively to face negative massage and misinformation. The media has to fact check on the misinformation and disinformation.

• Journal of Internet Computing and Services
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• v.19 no.4
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• pp.15-26
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• 2018

This study focused on the difference of the volume of sanitory pad issue and The aim of this study is to explore the relationship between the characteristics of SNS and the diffusion of issue in the process of crisis issue. SNS is categorized into communication diffusion, communication restriction,, diffusion, restriction base on the media interactivity and the user interactivity, In case of Twitter, media interactivity is low and user interactivity is low. In case of Youtube, media interactivity and user interactivity are all high. Crisiss issue is interactively diffused via Youtube compared to via Twitter. There was a negative public opinion in social media even if the government and the manufacturer said that there was no harm in the sanitary goods. In conclusion, this study highlights the importance of social media environment in the diffusion of information. The government prepared for the use of SNS in crisis because there was a negative opinion on the government and the manufacturer via SNS.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.5
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• pp.576-583
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• 2020

This paper proposes a technique to determine the spam comments on YouTube, which have recently seen tremendous growth. On YouTube, the spammers appeared to promote their channels or videos in popular videos or leave comments unrelated to the video, as it is possible to monetize through advertising. YouTube is running and operating its own spam blocking system, but still has failed to block them properly and efficiently. Therefore, we examined related studies on YouTube spam comment screening and conducted classification experiments with six different machine learning techniques (Decision tree, Logistic regression, Bernoulli Naive Bayes, Random Forest, Support vector machine with linear kernel, Support vector machine with Gaussian kernel) and ensemble model combining these techniques in the comment data from popular music videos - Psy, Katy Perry, LMFAO, Eminem and Shakira.

• The Journal of the Korea Contents Association
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• v.22 no.4
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• pp.222-230
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• 2022

Recently, Korea's cultural content industry is developing, and behind the growing recognition around the world is the real-time sharing service of global network users due to the development of science and technology. In particular, in the case of YouTube, its propagation power is fast and powerful in that everyone, not limited users, can become potential video providers. As more than 80% of mobile phone users are using YouTube in Korea, YouTube's information means that psychological factors of users are reflected. For example, information such as the number of video views, likes, and comments of a channel with a specific personality shows a measure of the channel's personality interest. This is highly related to the fact that information such as the frequency of keyword search on portal sites is closely related to the stock market economically and psychologically. Therefore, in this study, YouTube information from a representative entertainment company is collected through a crawling algorithm and analyzed for the causal relationship with major variables related to stock prices. This study is considered meaningful in that it conducted research by combining cultural content, IT, and financial fields in accordance with the era of the fourth industry.