• Journal of Korean Medical classics
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• v.20 no.3
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• pp.67-77
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• 2007

Through the translation and comparative study of the enriching blood and nourishing vital essence(補陰血方劑) in "The Elimination & Supplement about the Famous Prescription Comments(刪補名醫方論)" of "The Golden Mirror of Medicine(醫宗金鑑)" with "The Famous Prescription Comments on Ancient and Modern Times(古今名醫方論)", we confirmed that about 50% of the sentences from "The Elimination & Supplement about the Famous Prescription Comments(刪補名醫方論)" were quoted in "The Famous Prescription Comments on Ancient and Modern Times(古今名醫方論)", and that many of the text were not quoted unchanged, but were revised and supplemented. In organization, the prescription with the fewer number of component drugs is given first, followed by that with more component drugs, and that with similar component drugs is explained subsequently to facilitate understanding. In the prescription notes, it is emphasized that when enriching blood, the invigorative method(補氣法) is very important and that cold or pungent herb should be very carefully used.

• Knowledge Management Research
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• v.19 no.2
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• pp.91-108
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• 2018

This study mainly focused on measuring the impact of comments for a particular song on the number of streamings and downloads. We modeled multiple regression equations to perform this analysis. We chose digital music market for the object of analysis because of its inherent characteristics, such as experience goods, high bandwagon effect, and so on. We carefully utilized text mining technique in accordance with the algorithm of Naïve Bayes classifier to distinguish whether a comment for a piece of music be regarded as positive or negative. In addition, we used 'size of agency' and 'existence of hit song' as moderating variables. The reason for usage of those variables is that those are assumed to affect users' decision for selecting particular song especially when downloading or streaming via music sites. We found empirical evidences that positive comments for a particular song increase the number of both downloads and streamings. However, positive comments may decrease the number of downloads when the size of agency of the artist is big. As a result, we were able to say that a positive comment for a particular song functioned as 'word-of-mouth' effect, inducing other users' behavioral response. We also found that other features of an artist such as size of the agency that the artist belongs to functioned as an external factor along with feature of the song itself.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.11
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• pp.5321-5334
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• 2019

Data mining technology is frequently used in identifying the intention of users over a variety of information contexts. Since relevant terms are mainly hidden in text data, it is necessary to extract them. Quantification is required in order to interpret user preference in association with other structured data. This paper proposes rating and comments mining to identify user priority and obtain improved ratings. Structured data (location and rating) and unstructured data (comments) are collected and priority is derived by analyzing statistics and employing TF-IDF. In addition, the improved ratings are generated by applying priority categories based on materialized ratings through Sentiment-Oriented Point-wise Mutual Information (SO-PMI)-based emotion analysis. In this paper, an experiment was carried out by collecting ratings and comments on "place" and by applying them. We confirmed that the proposed mining method is 1.2 times better than the conventional methods that do not reflect priorities and that the performance is improved to almost 2 times when the number to be predicted is small.

• The Journal of the Korea Contents Association
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• v.10 no.8
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• pp.38-50
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• 2010

In recent years, the number of users who are actively express their opinions about Internet articles is more and more growing up, as the use of cyber community such as weblog or Internet discussion board increases. In fact, it is not difficult to find an article with hundreds of comments in famous Internet discussion boards. Most of the weblogs or Internet discussion boards present comments in the form of list and do not yet support even the basic operation such as searching comments. In this paper, we analysed large sets of comments in Internet discussion board named AGORA. It was found that from the result that the distribution of comment writers follows power-law. So we suppose a new search structure of comments using skip lists. The main idea of our approach is to reflect the probabilistic distribution properties of the commenters following the power-law to the data structure. Our empirical results show that the proposed method performs more efficient in searching the nodes with fewer number of comparison operations than logN, which is the theoretical time complexity of general indexed structure such as B-trees or typical skip lists.

• Nuclear Engineering and Technology
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• v.53 no.3
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• pp.1013-1019
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• 2021

This paper reviewed the temporal changes in the public opinions on nuclear energy in Korea with a big data analysis of nuclear energy-related articles and their comments posted on the portal site NAVER. All articles that included at least one of "nuclear energy," "nuclear power plant (NPP)," "nuclear power phase-out," or "anti-nuclear" in their titles or main text were extracted from those posted on NAVER in January 2010-December 2019. First, we performed annual word frequency analysis to identify what words had appeared most frequently in the articles. For that period, the most frequent words were "NPP," "nuclear energy," and "energy." In addition, "safety" has remained in the upper ranks since the Fukushima NPP accident. Then, we performed sentiment analysis of the pre-processed articles. The sentiment analysis showed that positive-tone articles have been reported more frequently than negativetone over the entire analysis period. Last, we performed sentiment analysis of the comments on the articles to examine the public's intention regarding nuclear issues. The analysis showed that the number of negative comments to articles each month-irrespective of positive or negative tone-was always larger than that of positive comments over the entire analysis period.

• Journal of Korea Society of Digital Industry and Information Management
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• v.12 no.4
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• pp.163-169
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• 2016

This study is to analyze factors affecting a growth of online community with perspectives of social network. Particularly this study tries to explore structural phenomenon built by interactions between users in a certain of free board belonging to the online community, in which focuses on one's writing a comments responding on those of others. With using SNA(Social Network Analysis), the social network data calculated from users' interaction shown as their comments were collected to draw out each individual's centrality value representing the structure of the online community and also we estimated duration time and the number of each comments as a proxy variable representing growth of the online community. And then cause-and-effect relationship between individual's centrality value and the duration time and the number of each comment were analyzed. As a result of the analysis, Core-Periphery, Centralization and Reciprocity have significant effects on the duration time and the number of each comment, therefore those significant values representing online structure will give an implication to manage, to promote the online community, to forecast its evolution path and to build critical policies.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.7
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• pp.92-101
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• 2017

The SNS website can take full advantage of the characteristics of users to conduct e-commerce. The e-commerce website's organizing ability will be greatly strengthened by SNS and creates greater value for consumers. This article examined the Chinese largest SNS (Weibo) users as research objects, and combined the development status of SNS in China. This article focuses on the influence to consumer's purchase intention in three aspects: number of comments, consumer involvement level, and consumer appealing method and examines how the interaction of the number of comments and consumer appealing method affects the purchase intention. An investigation was conducted on 400 users of SNS and using valid questionnaires to perform reliability analysis, validity analysis, independent sample t-test, and double factor variance analysis using SPSS21. The research results indicated that the number of comments and rational appealing method had significant effect on the purchase intention. The mediating or controlling the purchase involvement level will disturb the influence of the number of comments but will have no effect on the information appealing method.

• Journal of Korea Society of Industrial Information Systems
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• v.27 no.2
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• pp.25-34
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• 2022

With the development of online services, the ripple effect of negative comments is increasing, and the damage of cyber violence is rising. Various methods such as filtering based on forbidden words and reporting systems prevent this, but it is challenging to eradicate negative comments. Therefore, this study aimed to increase the accuracy of the classification of negative comments using deep learning and blur the parts corresponding to profanity. Two different conditional training helped decide the number of deep learning layers and filters. The accuracy of 88% confirmed with 90% of the dataset for training and 10% for tests. In addition, Grad-CAM enabled us to find and blur the location of swear words in negative comments. Although the accuracy of classifying comments based on simple forbidden words was 56%, it was found that blurring negative comments through the deep learning model was more effective.

• Journal of the Korean BIBLIA Society for library and Information Science
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• v.27 no.4
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• pp.63-84
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• 2016

This study aimed to investigate the extent that users participated in Facebook of U.S. state archives and the types of user responses to posts on the Facebook. For the purpose, data created between August 1st and September 30th in 2016 were collected from Facebook continuously operated by 27 state archives. The extent of user participation was measured based on the number of user comments, the number of unique commenters, and the average number of comments per post. According to the measures, top 10 Facebook of state archives were selected. Out of these, Facebook of Ohio (1st), Florida (5th) and Arkansas (10th) state archives were chosen to collect 687 user comments and 132 posts. The analysis showed that comments regarding users' emotional opinion and judgement, adding explanations to a post, and sharing personal stories occupied a large portion. Interactions among users or between a user and an archivist were also identified. With regard to posts, those for sharing information/knowledge of records held in archives were identified as a high percentage. The study suggested that archives should collect and present historical information and related records connected to users' lives, examine methods for effective communication with users via social media and facilitate publicity and outreach services of archives based on shaping and maintaining online user community through social media.

• Asia pacific journal of information systems
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• v.30 no.2
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• pp.420-438
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• 2020

Recently, with the advance of the wireless Internet access via mobile devices, a myriad of game development companies have forayed into the mobile game market, leading to intense competition. To survive in this fierce competition, mobile game developers often try to get a grasp of the rapidly changing needs of their customers by operating their own official communities where game users freely leave their requests, suggestions, and ideas relevant to focal games. Based on the heuristic-systematic model (HSM) and the data quality (DQ) framework, this study derives key content, non-content, and hybrid cues that can be utilized when game developers accept suggested postings in these online communities. The results of hierarchical multiple regression analysis show that relevancy, timeliness, amount of writing, and the number of comments are positively associated with mobile game developers' knowledge adoption. In addition, title attractiveness mitigates the relationship between amount of writing/the number of comments and knowledge adoption.