• The Journal of the Korea Contents Association
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• v.21 no.3
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• pp.364-374
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• 2021

In a fiercely competitive market, brands have become an important foundation for people to choose their products, and brands are also symbols of people's status and strength. Therefore, the importance of brand image design is growing. And color is an expression of emotion and can improve the communication and marketing environment of brand image as an important element of brand image. In this study, Interbrand selected Korea-China TOP 50 brand as a survey target in 2019 and downloaded brand CI from each brand's homepage to data images through Adobe Photoshop program and HSB system, and analyzed the color of the brand. There is no big difference in analyzing the color characteristics of Korean and Chinese brands, and the I.R.I color image scale analysis shows that the overall design of Korean brands is vibrant, elegant and warm to consumers. On the other hand, the overall design of the Chinese brand offers consumers a solemn, modern and sophisticated emotional adjective. Based on the results, this study can provide practical implications for companies to select colors and forms when launching their own brands and developing products.

• Science of Emotion and Sensibility
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• v.12 no.4
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• pp.433-442
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• 2009

People are tending to buy products through the Internet rather than purchasing them from the store. Some of the consumers give their feedback on line such as reviews, replies, comments, and blogs after they purchased the products. People are also likely to get some information through the Internet. Therefore, companies and public institutes have been facing this situation where they need to collect and analyze reviews or public opinions for them because many consumers are interested in other's opinions when they are about to make a purchase. However, most of the people's reviews on web site are too numerous, short and redundant. Under these circumstances, the emotion scanning system of text documents on the web is rising to the surface. Extracting writer's opinions or subjective ideas from text exists labeled words like GI(General Inquirer) and LKB(Lexical Knowledge base of near synonym difference) in English, however Korean language is not provided yet. In this paper, we labeled positive, negative, and neutral attribute at 4 POS(part of speech) which are noun, adjective, verb, and adverb in Korean dictionary. We extract construction patterns of emotional words and relationships among words in sentences from a large training set, and learned them. Based on this knowledge, comments and reviews regarding products are classified into two classes polarities with positive and negative using SO-PMI, which found the optimal condition from a combination of 4 POS. Lastly, in the design of the system, a flexible user interface is designed to add or edit the emotional words, the construction patterns related to emotions, and relationships among the words.

• Science of Emotion and Sensibility
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• v.15 no.1
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• pp.87-96
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• 2012

This paper proposes a Image retrieval system that searches the closest images to the user's emotional need and displays images with higher ratings of color harmony from Moon-Spencer's Color Harmony Theory first. Once an emotional adjective is placed, the system searches for images with colors that contain more elements derived from Aesthetic Measure results and displays in such order. In order to test reliability of the proposed emotion retrieval method based on Moon-Spencer's Color Harmony Theory, this study compared the order of Aesthetic Measure results with the user satisfaction ratings using 200 sample images. The analysis demonstrated that the participants' average satisfaction on 15 emotion adjectives selected for the study was 5.0 on a 7-point Likert scale. Correlation analyses were performed to test the consistency the orders between Aesthetic Measure values and user satisfaction ratings. Positive correlations above R=.5 were observed in all 14 emotion words except "Clear". These findings prove the potential of the proposed emotion retrieval system based on Moon-Spencer's Color Harmony Theory to effectively reflect user emotion in such visual stimulus search as image database.

• Journal of Intelligence and Information Systems
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• v.21 no.2
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• pp.69-92
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• 2015

The explosion of social media data has led to apply text-mining techniques to analyze big social media data in a more rigorous manner. Even if social media text analysis algorithms were improved, previous approaches to social media text analysis have some limitations. In the field of sentiment analysis of social media written in Korean, there are two typical approaches. One is the linguistic approach using machine learning, which is the most common approach. Some studies have been conducted by adding grammatical factors to feature sets for training classification model. The other approach adopts the semantic analysis method to sentiment analysis, but this approach is mainly applied to English texts. To overcome these limitations, this study applies the Word2Vec algorithm which is an extension of the neural network algorithms to deal with more extensive semantic features that were underestimated in existing sentiment analysis. The result from adopting the Word2Vec algorithm is compared to the result from co-occurrence analysis to identify the difference between two approaches. The results show that the distribution related word extracted by Word2Vec algorithm in that the words represent some emotion about the keyword used are three times more than extracted by co-occurrence analysis. The reason of the difference between two results comes from Word2Vec's semantic features vectorization. Therefore, it is possible to say that Word2Vec algorithm is able to catch the hidden related words which have not been found in traditional analysis. In addition, Part Of Speech (POS) tagging for Korean is used to detect adjective as "emotional word" in Korean. In addition, the emotion words extracted from the text are converted into word vector by the Word2Vec algorithm to find related words. Among these related words, noun words are selected because each word of them would have causal relationship with "emotional word" in the sentence. The process of extracting these trigger factor of emotional word is named "Emotion Trigger" in this study. As a case study, the datasets used in the study are collected by searching using three keywords: professor, prosecutor, and doctor in that these keywords contain rich public emotion and opinion. Advanced data collecting was conducted to select secondary keywords for data gathering. The secondary keywords for each keyword used to gather the data to be used in actual analysis are followed: Professor (sexual assault, misappropriation of research money, recruitment irregularities, polifessor), Doctor (Shin hae-chul sky hospital, drinking and plastic surgery, rebate) Prosecutor (lewd behavior, sponsor). The size of the text data is about to 100,000(Professor: 25720, Doctor: 35110, Prosecutor: 43225) and the data are gathered from news, blog, and twitter to reflect various level of public emotion into text data analysis. As a visualization method, Gephi (http://gephi.github.io) was used and every program used in text processing and analysis are java coding. The contributions of this study are as follows: First, different approaches for sentiment analysis are integrated to overcome the limitations of existing approaches. Secondly, finding Emotion Trigger can detect the hidden connections to public emotion which existing method cannot detect. Finally, the approach used in this study could be generalized regardless of types of text data. The limitation of this study is that it is hard to say the word extracted by Emotion Trigger processing has significantly causal relationship with emotional word in a sentence. The future study will be conducted to clarify the causal relationship between emotional words and the words extracted by Emotion Trigger by comparing with the relationships manually tagged. Furthermore, the text data used in Emotion Trigger are twitter, so the data have a number of distinct features which we did not deal with in this study. These features will be considered in further study.

• The Journal of the Korea Contents Association
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• v.10 no.6
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• pp.286-296
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• 2010

The study of the development of DJ robots is to meet the demands of the music services which are changing very rapidly in the digital and network era. Existing studies, as a whole, develop music services on the premise of personalized environment and equipment, but the DJ robot is on the premise of the open space shared by the public. DJ robot gives priority to traditional space and music. Recently as the hospitality and demand for cultural contents of South Korea expand to worldwide, industrial use of the contents based on traditional or our unique characteristics is getting more and more. Meanwhile, the DJ robot is composed of a combination of two modules. One is to detect changes in the external environment and the other is to set the properties of the music by psychology, emotional engineering, etc. DJ robot detect the footprint of the temperature, humidity, illumination, wind, noise and other environmental factors measured, and will ensure the objectivity of the music source by repeated experiments and verification with human sensibility ergonomics based on Hevner Adjective Circle. DJ robot will change the soundscape of the traditional space being more beautiful and make the revival and prosperity of traditional music with the use of traditional music through BGM.

• Science of Emotion and Sensibility
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• v.12 no.1
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• pp.121-128
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• 2009

The article reports findings on: (1) development of emotion assessment scale in evaluating the Television(TV) picture quality; and (2) how psychological and physical factors relate to TV picture quality. A total of 152 adjectives that specifically describe emotional reactions were first selected from a Korean dictionary of adjectives, followed by ratings on their suitability for the evaluation of TV picture quality. The final selection of 19 adjective, based on the reported rating scores greater than 4.1, were used on 126 college students who were asked to perform similarity ratings on the adjectives. Based on factor analyses (i.e., principal component analysis with oblique rotation) on the similarity of scores, the following adjectives were selectively chosen for the development of the new emotion assessment scale: 'neat-messy', 'refreshing-gloomy', 'clean-dirty', 'comfortable-tense', 'smooth-rough', 'bright-dark', 'gorgeous-plain', 'diverse-monotonous', 'satisfying', 'natural', and 'sensuous'. These adjectives composed into two distinct constructs, 'cleanness or smart' factor and 'gorgeousness' factor, which demonstrated sensitivity to changes in brightness, contrast, color, and tint in the TV picture quality, except for changes in sharpness.

• The Journal of the Korea Contents Association
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• v.19 no.1
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• pp.548-558
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• 2019

Along generalization of internet news comments, malicious comments have been spread and made many social problems. Because writings reflect human mental state or trait, analyzing malicious comments, human mental states could be inferred when they write internet news comments. In this study, we analyzed malicious comments of English and Korean speaker using LIWC and KLIWC. As a result, in both English and Korean, malicious comments are commonly more used in sentence, word phrase, morpheme, word phrase per sentence, morpheme per sentence, positive emotion words, and cognitive process words than normal comments, and less used in the third person singular, adjective, anger words, and emotional process words than normal comments. This means people are state that they can not control their feeling such as anger and can not think well when they write news comments. Therefore, when internet comments were written, service provider should consider the way that commenters monitor own writings by themselves and that they prevent the other users from getting close to comments included many negative-emotion words. In other sides, it is discovered that English and Korean malicious comments was discriminated by authenticity. In order to be more objective, gathering data from various point of time is needed.

• Smart Media Journal
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• v.9 no.4
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• pp.144-151
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• 2020

In a mobile environment, communication takes place via SMS text messages. Vocabularies used in SMS texts can be expected to use vocabularies of different classes from those used in general Korean literary style sentence. For example, in the case of a typical literary style, the sentence is correctly initiated or terminated and the sentence is well constructed, while SMS text corpus often replaces the component with an omission and a brief representation. To analyze these vocabulary usage characteristics, the existing colloquial style corpus and the literary style corpus are used. The experiment compares and analyzes the vocabulary use characteristics of the colloquial corpus SMS text corpus and the Naver Sentiment Movie Corpus, and the written Korean written corpus. For the comparison and analysis of vocabulary for each corpus, the part of speech tag adjective (VA) was used as a standard, and a distinctive collexeme analysis method was used to measure collostructural strength. As a result, it was confirmed that adjectives related to emotional expression such as'good-','sorry-', and'joy-' were preferred in the SMS text corpus, while adjectives related to evaluation expressions were preferred in the Naver Sentiment Movie Corpus. The word embedding was used to automatically construct a sentiment lexicon based on the extracted adjectives with high collostructural strength, and a total of 343,603 sentiment representations were automatically built.

• (The) Research of the performance art and culture
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• no.22
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• pp.123-155
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• 2011

This study aims to closely read Kim Jong-il's "About Stage Drama Arts" and disclose the new reality as evaluated by him. The study took the method by which to compare Kim Jong-il's theory on drama and North Korea's drama theory in the 1950s, and the findings of this study revealed that it was irrational to grant the adjective "new" to Kim Jong-il's drama theory. This is because tradition inheritance and newness cross each other. First, his tradition inheritance aspect was found in his playwriting method. In playwriting method, Kim Jong-il's argument about characters and language is an extension of the 1950s drama theory, and his theory on JongZa(seeds) is the transformation of the concept proposed in the 1950s. Also, the expression means of dramas and drama arts is dialogue, and his guideline to focus on the art of conversation rather than on acting is interpreted to be a reduced concept of drama arts, compared with the 1950s drama theory. On the other hand, his newness aspect can be clearly discovered in the materialization of stage. The fixed stage background, without dark change, shifts to another situation as it is, and this stage setting is clearly distinguished from the previous stage setting. The attempt is worth highly evaluating to allow the stage to reflect actors' emotional flows and let them act. Also, the attempt is distinctively distinguished from previous drama theories to allow the chorus' positive involvement in dramas so as to directly deliver characters' emotions to the audience and to trigger the audience' response as intended by creators. From the perspectives of drama evaluation, Kim Jong-il's theory and practice regarding stage and music is understood to maximize the audio-visual effects. Therefore, Kim Jeong-il's drama theory, as he argues, is not a completely new theory, but a transformational inheritance of existing drama theories, and a creation theory with focus on expansion of spectacles.