• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.12
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• pp.1880-1889
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• 2022

The online portal platform provides online news with online comments, but the anonymity of comments causes incivility, and online comments are considered social problems. While there are many foreign language-based incivility detection studies, in-depth research is not being conducted in Korea since there has not been implemented Korean language dataset which is labeled detailed criteria of incivility. In this study, the incivility notation of comments was conducted in a total of 13 items, uncivil words were summarized. Furthermore, Attention algorithm was applied to each comment and summary to extract embedding vectors. 2-d CNN followed at the end to detect incivility in given data. As a result, we showed that the proposed algorithm is useful for anti-citizen detection such as name-calling and offensive tones. This study is expected to contribute to the formation of a healthy online comment culture by detecting uncivil comments which hinder democratic discourse.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.18 no.2
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• pp.263-283
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• 2024

Users' comments after online shopping are critical to product reputation and business improvement. These comments, sometimes known as e-commerce reviews, influence other customers' purchasing decisions. To confront large amounts of e-commerce reviews, automatic analysis based on machine learning and deep learning draws more and more attention. A core task therein is sentiment analysis. However, the e-commerce reviews exhibit the following characteristics: (1) inconsistency between comment content and the star rating; (2) a large number of unlabeled data, i.e., comments without a star rating, and (3) the data imbalance caused by the sparse negative comments. This paper employs Bidirectional Encoder Representation from Transformers (BERT), one of the best natural language processing models, as the base model. According to the above data characteristics, we propose the F_MixBERT framework, to more effectively use inconsistently low-quality and unlabeled data and resolve the problem of data imbalance. In the framework, the proposed MixBERT incorporates the MixMatch approach into BERT's high-dimensional vectors to train the unlabeled and low-quality data with generated pseudo labels. Meanwhile, data imbalance is resolved by Focal loss, which penalizes the contribution of large-scale data and easily-identifiable data to total loss. Comparative experiments demonstrate that the proposed framework outperforms BERT and MixBERT for sentiment analysis of e-commerce comments.

• The Journal of Information Systems
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• v.32 no.4
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• pp.29-50
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• 2023

Purpose The impact of online reviews is widely acknowledged, with extensive research focused on text-based reviews. However, there's a lack of research regarding reviews in video format. To address this gap, this study aims to explore the connection between company-sponsored product review videos and the extent of directive speech within them. This article analyzed viewer sentiments expressed in video comments based on the level of directive speech used by the presenter. Design/methodology/approach This study involved analyzing speech acts in review videos based on sponsorship and examining consumer reactions through sentiment analysis of comments. We used Speech Act theory to perform the analysis. Findings YouTubers who receive company sponsorship for review videos tend to employ more directive speech. Furthermore, this increased use of directive speech is associated with a higher occurrence of negative consumer comments. This study's outcomes are valuable for the realm of user-generated content and natural language processing, offering practical insights for YouTube marketing strategies.

• Journal of the Korean Society for information Management
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• v.39 no.1
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• pp.257-280
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• 2022

In this study, we analyzed comments on news articles of representative companies of the three industries (i.e., semiconductor, secondary battery, and bio industries) that had been listed as national strategic technology projects of South Korea to identify public opinions towards them. In addition, we analyzed the relationship between changes in public opinion and stock price. 'Samsung Electronics' and 'SK Hynix' in the semiconductor industry, 'Samsung SDI' and 'LG Chem' in the secondary battery industry, and 'Samsung Biologics' and 'Celltrion' in the bio-industry were selected as the representative companies and 47,452 comments of news articles about the companies that had been published from January 1, 2020, to December 31, 2020, were collected from Naver News. The comments were grouped into positive, neutral, and negative emotions, and the dynamic topics of comments over time in each group were analyzed to identify the trends of public opinion in each industry. As a result, in the case of the semiconductor industry, investment, COVID-19 related issues, trust in large companies such as Samsung Electronics, and mention of the damage caused by changes in government policy were the topics. In the case of secondary battery industries, references to investment, battery, and corporate issues were the topics. In the case of bio-industries, references to investment, COVID-19 related issues, and corporate issues were the topics. Next, to understand whether the sentiment of the comments is related to the actual stock price, for each company, the changes in the stock price and the sentiment values of the comments were compared and analyzed using visual analytics. As a result, we found a clear relationship between the changes in the sentiment value of public opinion and the stock price through the similar patterns shown in the change graphs. This study analyzed comments on news articles that are highly related to stock price, identified changes in public opinion trends in the COVID-19 era, and provided objective feedback to government agencies' policymaking.

• Journal of Physiology & Pathology in Korean Medicine
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• v.19 no.1
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• pp.8-14
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• 2005

This paper is mainly on the medical comments in ${\ulcorner}$Sanbeon-bang(刪繁方)${\lrcorner}$. Among the medical comments in ${\ulcorner}Sanbeon-bang{\lrcorner}$, the Ojang-noron(五臟勞論) which deals with the Hanyeolheosil(寒熱虛實) of Ojang(五臟) and Yukgeuknon(六極論) which deals with the Hanyeolheosil of 'Geun-Maek-Yuk-Gi-Gol-Jeong(筋脈肉氣骨精)', remain perfectly. By way of these theories, it argues on various types of pathogenic states and syndromes. Related to the Ojang-noron, ${\ulcorner}Sanbeon-bang{\lrcorner}$ suggests a characteristic tonifying method which is 'Exhaustion syndromes should tonify the son organ(勞則補子法)'. It is the supplement of traditional 'Reinforcing the mother organ when treating cases of deficiency(虛則補其母)'. With the Ojang-noron, the comments about 'Samcho(三焦)' remain relatively intact in ${\ulcorner}Sanbeon-bang{\lrcorner}$. The contents are based on ${\ulcorner}$Yeongchu Yeongwisaenghoe(靈樞 營衛生會)${\lrcorner}$, combined the contents of ${\ulcorner}$Nangyeong 31st difficulty(難經 三十一難)${\lrcorner}$ and the meridian line in ${\ulcorner}$Yeongchu Gyeongmaek(靈樞 經脈)${\lrcorner}$. They were quoted untouched in ${\lrcorner}Cheongeumyo-bang{\lrcorner}$ by Son Sa-mak, and became the fundamental structure of Samcho-theory of after ages. Among the medical comments in ${\ulcorner}Sanbeon-bang{\lrcorner}$, there has been much dispute over the problem about 'Chu-Tae-eum(秋太陰), Dong-So-eum(冬少陰)'. This study will pay attention to the connection between Wang Bing's views of ${\ulcorner}Sanbeon-bang{\lrcorner}$ for compilation of ${\ulcorner}Chaju-Hwangje-Naegyeong-Somun{\lrcorner}$ and the original ${\ulcorner}Sanbeon-bang{\lrcorner}$. Judging from this study, Wang Bing may have referred to ${\ulcorner}Sanbeon-bang{\lrcorner}$, ${\ulcorner}Oedaebiyo-bang{\lrcorner}$ or another medical book of similar stock, and from this he may have reconstructed the attribute of Eum-Yang(陰陽) which is related to Pye and Sin. Wang Bing's disciples may have referred to ${\ulcorner}Sanbeon-bang{\lrcorner}$, or with Wang Do, the writer of ${\ulcorner}Oedaebiyo-bang{\lrcorner}$, building up the main medical current in those days.

• The Journal of the Convergence on Culture Technology
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• v.10 no.1
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• pp.419-425
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• 2024

As digital communication gains prominence, there is an increasing trend in uncivil behaviors like rude or hateful comments and the empathetic actions towards them, highlighting the need for social efforts to address these issues. As part of these endeavors, we investigated how avatar feedback in a virtual news portal affects users' empathy towards uncivil comments. We defined both posting and empathizing with uncivil comments as antisocial actions. To this end, we posted socially controversial news in a virtual space and provided feedback in two forms when participants selected uncivil comments: text-only feedback and feedback accompanied by an avatar. We then assessed the impact of this feedback on behavioral conformity, guilt, and self-image concern through surveys. Our results showed that avatar-provided feedback significantly influenced participants' social responses more than text-based feedback. Interaction with avatars notably increased participants' behavioral conformity, guilt, and self-image concern. We concluded that avatar-based interactions can positively influence users' social behaviors and attitudes, suggesting their potential in fostering a more civil and responsible digital communication culture.

• Informatization Policy
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• v.31 no.1
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• pp.3-31
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• 2024

This study aimed to examine public concerns in South Korea considering the country's unique context, triggered by the advent of generative artificial intelligence such as ChatGPT. To achieve this, comments from 102 YouTube video news related to ethical issues were collected using a Python scraper, and morphological analysis and preprocessing were carried out using Textom on 15,735 comments. These comments were then analyzed using a Correlated Topic Model (CTM). The analysis identified six primary topics within the comments: "Legal and Ethical Considerations"; "Intellectual Property and Technology"; "Technological Advancement and the Future of Humanity"; "Potential of AI in Information Processing"; "Emotional Intelligence and Ethical Regulations in AI"; and "Human Imitation."Structuring these topics based on a correlation coefficient value of over 10% revealed 3 main categories: "Legal and Ethical Considerations"; "Issues Related to Data Generation by ChatGPT (Intellectual Property and Technology, Potential of AI in Information Processing, and Human Imitation)"; and "Fear for the Future of Humanity (Technological Advancement and the Future of Humanity, Emotional Intelligence, and Ethical Regulations in AI)."The study confirmed the coexistence of various concerns along with the growing interest in generative AI like ChatGPT, including worries specific to the historical and social context of South Korea. These findings suggest the need for national-level efforts to ensure data fairness.

• Journal of the Korean Ceramic Society
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• v.37 no.7
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• pp.726-729
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• 2000

The entitled report revealed that ZnO phosphor samples treated at different temperatures under a given reduction atmosphere show the radiation brightness increase with increase of temperature up to about 900$^{\circ}C$ but become decreasing beyond the temperature. The brightness deterioration with curing temperature at higher temperatures was explained by the decrease of excess zinc ions resulted from their evaporation. The comments will open possibility for different discussions on the experimental result by introducing numerical relationships between the concentration of the native defects and the curing condition.

• Journal of Korean Neurosurgical Society
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• v.62 no.3
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• pp.288-295
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• 2019

In 2011, the International League against Epilepsy (ILAE) proposed a first international consensus of the classification of focal cortical dysplasia (FCD). This FCD classification had been widely used in worldwide. In this review paper, the authors would like to give helpful comments for better understanding of the current FCD classification. Especially, the basic concepts of FCD type I, such as "radial", "tangential" and "microcolumn" will be discussed with figures. In addition, the limitations, genetic progress and prospect of FCD will be suggested.

• The Journal of the Korea Contents Association
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• v.9 no.7
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• pp.45-56
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• 2009

There are many internet users who collect the public opinions and express their opinions for internet news or blog articles through the replying comment on online community. But, it is hard to search and explore useful messages on web blogs since most of web blog systems show articles and their comments to the form of sequential list. Also, spam and malicious comments have become social problems as the internet users increase. In this paper, we propose a clustering and visualizing system for responding comments on large-scale weblogs, namely 'Daum AGORA,' using similarity analysis. Our system shows the comment clustering result as a simple screen view. Our system also detects spam comments using Needleman-Wunsch algorithm that is a well-known algorithm in bioinformatics.