• Science of Emotion and Sensibility
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• v.19 no.3
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• pp.121-132
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• 2016

Emotion is considered to be involved in the moral decision-making process consisting of moral judgment, moral intention, and moral behavior. This research investigated the distinct role of two specific moral emotions, guilt and shame, when they are suppressed, on moral judgment, moral intention, and moral behavior through an online experiment. Moral emotion (guilt vs. shame) as well as suppression of these emotions (suppressing vs. control) was manipulated to infer the causality of moral emotions and the moral decision-making process when they are suppressed. The results suggest that suppressing guilt was involved in moral judgment and moral intention, but was not involved in moral behavior. In particular, participants who maintained guilt evaluated moral vignettes as more moral and perceived that they would follow the behavior described in the vignettes than those participants who suppressed their guilt. On the other hand, our data showed that suppressing shame was not involved in moral judgment and intention but was in behavior. Participants who maintained shame engaged in moral behavior more than participants who suppressed shame. We delineate the different mechanisms between guilt and shame on the moral decision-making process with the discrete emotion theory.

• Korean journal of communication and information
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• v.52
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• pp.48-68
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• 2010

In covering the controversies surrounding the so-called cyber defamation laws, the Korean press offered competitive frames in terms of values (security vs. freedom of speech) and attributional patterns (episodic vs. thematic attribution). By attending to core values and attributional patterns as two essential components of news frames, this study explored the cognitive and affective processes of value and attributional framing and their effects on issue opinion. According to a 3-group online experiment, first, it was found that core values increased the perceived importance of relevant beliefs, which further affected individuals' attitudes toward the laws. The affective effects of core values were also found marginally significant. The value of security increased the intensity of anger toward deviant netizens (so-called defamatory repliers), and it further increased individuals' support for the laws. It was not substantiated, however, that individualistic attribution, than social attribution, would provoke stronger anger toward defamatory repliers. Instead, episodic frames appeared to be more effective in driving issue opinion as indicated by the value frame.

• The Journal of Society for e-Business Studies
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• v.22 no.1
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• pp.65-87
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• 2017

We propose a method to analyze the user reviews and ratings of the products in the online shopping mall and automatically extracts the features of the products to determine the characteristics of a product. By judging whether a rating is given by a specific feature of a product, our method distributes the score to each feature. Conventional methods force users to wastes time reading overflowing number of reviews and ratings to decide whether to buy the product or not. Moreover, it is difficult to grasp the merits and demerits of the product, because of the way reviews and ratings are provided. It is structured in a way that it is impossible to decide which rating is given to the which characteristics of the product. Therefore, in this paper, to resolve this problem, we propose a method to automatically extract the feature of the product from the user review and distribute the score to appropriate characteristics of the product by calculating the rating of each feature from the overall rating. proposed method collects product reviews and ratings, conducts morphological analysis, and extracts features and emotional words of the products. In addition, a method for determining the polarity of a sentence in which the feature appears is given a weight value for each feature. results of the experiment and the questionnaires comparing the existing methods show the usefulness of the proposed method. We also validates the results by comparing the analysis conducted by the product review experts.

• Journal of KIISE:Databases
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• v.35 no.5
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• pp.421-431
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• 2008

Recently XML is becoming a de facto standard for online data exchange between heterogeneous systems and also the research of streaming XML data filtering comes into the spotlight. Since streaming XML data filtering technique needs rapid matching of queries with XML data, it is required that the query processing should be efficiently performed. Until now, most of researches focused only on partial sharing of path expressions or efficient predicate processing and they were work for time and space efficiency. However, if containment relationship between queries is previously calculated and the lowest level query is matched with XML data, we can easily get a result that high level queries can match with the XML data without any other processing. That is, using this containment technique can be another optimal solution for streaming XML data filtering. In this paper, we suggest an efficient XML data filtering based on prime number indexing and containment relationship between queries. Through some experimental results, we present that our suggested method has a better performance than the existing method. All experiments have shown that our method has a more than two times better performance even though each experiment has its own distinct test purpose.

• The KIPS Transactions:PartD
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• v.14D no.4 s.114
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• pp.381-388
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• 2007

Consumers changed to the subject to produce a digital contents as data transmission technique is advanced and a digital machine is diffused variously. Users are interested greatly in a user creative movie (UCM) production among various online contents. The UCM production method which uses the music and picture is the method that users make the UCM more easily. However, the UCM production service has the problem that any association does not exist in the music and picture and that the picture changes according to fixed time interval without the relation at a music rhythm. To solve this problem, we propose the UCM production method which uses a music analysis and picture analysis in the paper. A music analysis finds a picture change time according to the rhythm and a picture analysis finds the association of the picture. A music analysis finds strong parts of the sound which uses Root-Mean-Square (RMS). And a picture analysis classifies the picture as a scenery picture and people picture which uses structure simplicity of the picture(SSP) and face region detection. A picture analysis got correct result of 86.4% in the experiment and we can finds the association at each picture and arranges the sequence which the picture appears. Therefore, if we use a music and picture analysis at the UCM production, users may make natural and efficient movie.

• Informatization Policy
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• v.19 no.2
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• pp.21-38
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• 2012

The proliferation of the Internet and the advent of e-commerce have amplified public concerns about privacy. Accordingly, much research effort has been made on the issue. While existing research on online information privacy has usually focused on the examination of antecedents of personal information disclosure, the literature has not paid attention to the potential changes of the antecedents' effects depending on the user's experience of the service. The current study aims to investigate the moderating role of site usage experience in Internet users' decision on personal information disclosure. Specifically, this study considers two types of antecedents of personal information disclosure on a site - the attributes of personal information requested (sensitivity and relevance of information) and the value of the service provided by the site; and examines how the effects of the antecedents on the disclosure intention are affected by the users'experience of the site. Our analysis of the data gathered through a web-based experiment reveals that site usage experience moderates the relationship between the attributes of personal information and disclosure intention. While usage experience attenuates the negative effect of information sensitivity on disclosure intention, it intensifies the positive impact that relevance of information has on disclosure intention. Based on the analysis results, we provide implications for the mitigation of the Internet users' privacy concerns as well as theoretical implications.

• The Transactions of the Korean Institute of Power Electronics
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• v.6 no.1
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• pp.98-106
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• 2001

This paper presents external load disturbance compensation that used to deadbeat load torque observer and regulation of the compensation gain by parameter estimator. As a result, the response of PMSM follows that of the nominal plant. The load torque compensation method is compose of a dead beat observer that is well-known method. However it has disadvantage such as a noise amplification effect. To reduce of the effect, the post-filter, which is implemented by MA process, is proposed. The parameter compensator with RLSM(recursive least square method) parameter estimator is suggested to increase the performance of the load torque observer and main controller. Although RLSM estimator is one of the most effective methods for online parameter identification, it is difficult to obtain unbiased result in this application. It is caused by disturbed dynamic model with external torque. The proposed RLSM estimator is combined with a high performance torque observer to resolve the problems. As a result, the proposed control system becomes a robust and precise system against the load torque and the parameter variation. A stability and usefulness, through the verified computer simulation and experiment, are shown in this paper.

• The Journal of the Korea Contents Association
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• v.19 no.7
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• pp.1-12
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• 2019

According to a survey on the frequency of access to medical ads by the Korea Press Foundation in 2017, the most commonly exposed ads among adult men and women are advertising about beauty, plasticity and obesity. As of 2011, South Korea had the largest number of cosmetic surgeries in the world, with 131 cosmetic surgeries per 10,000 people. As a result, as many as 1,414 plastic surgery clinics are operating in South Korea, and the number is also on the rise. Although there are various standards for evaluating people's appearance, the desire to pursue a better look is growing day by day. Then, one might wonder what factors influence consumers' choices among the numerous advertisements for plastic surgery clinics. Based on these questions, this study identified the examples of plastic surgery advertisements, analyzed their type, and identified the types of advertisements with the high visual appeal of the advertising consumer through eye tracking experiment. In total, seven eye-tracking tests of plastic surgery social media advertisements were conducted on 10 subjects. The results showed that the commercial model was the biggest factor that caught the attraction and attention of the ad recipient first and that the most focused and long-standing factor was the treatment contents. Therefore, it is important to select proper commercial models for hospital and clinic contents and to specify factual treatment contents when producing social media advertisements for plastic surgeons. We hope these findings will help create online advertising for plastic surgery clinics effectively.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.19 no.3
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• pp.9-15
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• 2019

Large global online shopping malls, such as Amazon, offer services in English or in the language of a country when their products are sold. Since many customers purchase products based on the product reviews, the shopping malls actively utilize the sentimental analysis technique in judging preference of each product using the large amount of review data that the customer has written. And the result of such analysis can be used for the marketing to look the potential shoppers. However, it is difficult to apply this English-based semantic analysis system to different languages used around the world. In this study, more than 500,000 data from Amazon fine food reviews was used for training a deep learning based system. First, sentiment analysis evaluation experiments were carried out with three models of English test data. Secondly, the same data was translated into seven languages (Korean, Japanese, Chinese, Vietnamese, French, German and English) and then the similar experiments were done. The result suggests that although the accuracy of the sentimental analysis was 2.77% lower than the average of the seven countries (91.59%) compared to the English (94.35%), it is believed that the results of the experiment can be used for practical applications.

• Journal of Digital Convergence
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• v.17 no.5
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• pp.137-143
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• 2019

Fake news is a form of misinformation that has the advantage of rapid spreading of information on media platforms that users interact with, such as social media. There has been a lot of social problems due to the recent increase in fake news. In this paper, we propose a method to detect such false news. Previous research on fake news detection mainly focused on text analysis. This research focuses on a network where social media news spreads, generates qualities with DeepWalk, a network embedding method, and classifies fake news using logistic regression analysis. We conducted an experiment on fake news detection using 211 news on the Internet and 1.2 million news diffusion network data. The results show that the accuracy of false network detection using network embedding is 10.6% higher than that of text analysis. In addition, fake news detection, which combines text analysis and network embedding, does not show an increase in accuracy over network embedding. The results of this study can be effectively applied to the detection of fake news that organizations spread online.