• The Journal of the Convergence on Culture Technology
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• v.8 no.6
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• pp.175-184
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• 2022

Travel YouTubers who cross the boundary between tradition and novelty communicate by sharing their activities with others through SNS-based media. Media content should not only satisfy individuals, nor should it be too purpose-oriented. YouTube channels should be operated so that users can easily access content naturally, and more diverse methods can be pursued based on usage patterns and satisfaction theory. This study is about the type of perception of Generation Z on travel YouTube titles. As a result of conducting QUANL program analysis on 34 Q samples and 28 P samples from the Q methodological perspective, a total of three types were found. For types with unique characteristics, the first type was named "attention of keywords that draw imagination," the second type was "preferred to stories that stimulate curiosity," and the third type was "image satisfaction reflecting expectations." In addition, considering the characteristics of each type found, the scalability and strategic plan of the activities that Generation Z travel YouTubers want to unfold were presented.

• The Journal of the Korea Contents Association
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• v.20 no.9
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• pp.169-186
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• 2020

This study aims to examine the characteristics of news content and users' reactions in local broadcasting Youtube news' channel, and explore how the local media should response in the new online video environment. YouTube Open API sampled 3,950 news-related videos uploaded over a month on 31 YouTube news channels nationwide. The content analysis was performed on the basis of the analysis of individual videos, such as characteristics of each content and users' reactions. As a result, a few news channels have produced digital-only content, but the ratio has been very low, most were broadcast replay videos with titles and formats uploaded as they were. In some cases, it still operates as a comprehensive channel, which failed to show its expertise as an independent digital news platform. This shows that theses YouTube channels lacks differentiation from TV or its own web page, and is still skewed to the auxiliary role or online archive function of TV platform. Nevertheless, digital-only content, which can be a national issue based on regional expertise, has led to a higher number of views and users reactions, suggesting that is a realistic and effective strategy with expandability in online space in the future.

• 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.

• Proceedings of the Korea Information Processing Society Conference
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• 2022.11a
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• pp.779-781
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• 2022

본 연구에서는 낚시성 콘텐츠의 주요 구성 요소인 썸네일과 제목을 MLKit와 TF-IDF를 이용하여 분석하고 이를 딥러닝 Sentence BERT 모델에 적용하였다. 이를 활용하여 추후 낚시성 콘텐츠를 걸러내는 알고리즘을 개발 예정이다.

• Proceedings of the Korean Society of Computer Information Conference
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• 2021.01a
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• pp.349-351
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• 2021

Youtube 동영상 업로드 시, 사용자가 직접 주제를 설정해야 하는 어려움이 있다. 본 연구에서는 사용자가 입력하는 제목과 설명정보를 이용하여 자동으로 주제를 분류하는 연구를 진행하였다. 이를 위해 한국어기반의 컨텐츠 중 고빈도의 8개 주제 카테고리를 선정하고, 이를 1.3만건의 학습데이터를 크롤링을 통해 구축하였다. 또한, 다양한 알고리즘들에 대한 최대성능을 확인하기 위해 대표적인 텍스트 분류 방법인 SVM과 LSTM기법 및 BERT 모델기반 미세적용(fine-tuning)을 시도하였다. 결과적으로 Bert-multiligual (base)를 fine-tuning한 실험에서 최대 94%의 정확도를 확인하였다. 하지만, Youtube 동영상 특성상 여러 주제를 가진 것들이 상당수 존재하기에, 실제 체감정확도는 더 높을 것으로 기대된다.

• Journal of Home Health Care Nursing
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• v.29 no.3
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• pp.278-287
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• 2022

Purpose: To analyze Korean nurse-related channels and video titles on YouTube, the world's largest online video sharing and social media platform, to clarify public opinion and image of nurses. We seek utilization strategies and measures through current status analysis. Methods: Data is collected by crawling video information related to Korean nurses, and correlation is analyzed with frequent word analysis and keyword network analysis. Results: Through the YouTube algorithm, 2,273 videos of 'Nurse' were analyzed in order of recent views, relevance, and rating, and 2,912 videos searched for with the keyword 'Nurse + Hospital, COVID-19, Awareness, University, National Examination' were analyzed. Numerous videos were uploaded, and nursing work that was uploaded in the form of a vlog recorded a high number of views. Conclusion: We could see if the YouTube video shows images of nurses. It has been confirmed that various information is being exchanged rather than information just for promotional purposes.

• Journal of KIISE
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• v.44 no.3
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• pp.287-294
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• 2017

With the personal-media development that has emerged through various means such as UCC and SNS, many media studies have been completed for the purposes of analysis and recognition, thereby improving the object-recognition level. The focus of these studies is a classification of media that is based on a recognition of the corresponding objects, rather than the use of the title, tag, and scripter information. The media-classification task, however, is intensive in terms of the consumption of time and energy because human experts need to model the underlying media ontology. This paper therefore proposes an automated approach for the modeling of the media-classification ontology schema; here, the OWL-DL Axiom that is based on the frequency of the recognized media-based objects is considered, and the automation of the ontology modeling is described. The authors conducted media-classification experiments across 15 YouTube-video categories, and the media-classification accuracy was measured through the application of the automated ontology-modeling approach. The promising experiment results show that 1500 actions were successfully classified from 15 media events with an 86 % accuracy.

• Journal of Science Education
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• v.42 no.3
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• pp.371-389
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• 2018

This study focuses on the fact that students and teachers commonly have difficulty in 'selecting the topic' in many activities including student-led research that is conducted from topic selection to the drawing of conclusion. The purpose of this study is to develop a manual for science teaching research. The instructional manuals of 4 stages were developed based on practical knowledge that can be implemented in the actual class through previous research and literature. Each stage is composed of , , , and . In the third stage, students are expected to find scientific questions and develop them into research topics through detailed class research on newspaper articles, scientific magazines, traditional knowledge, proverbs, daily life, and textbook experiments. In the experimental group, the final research topic was selected through a variety of sources such as textbook experiments, proverbs, YouTube images, newspaper articles, individual WHY NOTEs, and understood the conditions of the scientific research topic and expressed the variables in the research title. However, in the control group, some students did not consider the research scope of the selected research subjects to be specific or not to be able to study at their level. As a result of giving the students as much autonomy as possible, many groups did not fully understand the previous research and submitted it. Based on the results of this study, it can be concluded that development and use of a 'topic selection stage' centered practice manual for general high school teachers would not only improve the students' abilities to discover solutions to scientific questions, but it will also help shift their attitudes towards science in a positive direction.