• The Journal of the Convergence on Culture Technology
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• v.5 no.3
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• pp.79-84
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• 2019

Based on the assumption that the environmental color of the general hospital would affect the psychological and emotional aspects of the users, this study conducted an emotional evaluation of the environmental color of the lobby of the general hospital. The purpose of the research is to examine the requirements of environmental colors that are more positive and give psychological satisfaction when planning the general hospital's environmental color. For this, eight major general hospitals in Korea were directly inspected for environmental colors, and based on this, color palette was created to conduct an emotional vocabulary evaluation. As a result, it was found that the effects of brightness among the color factors affecting the environmental color sensitivity evaluation were greater, and that the greater the variation in the range of degrees and colors, the more negatively it was found to affect the emotional response.

• The Journal of the Korea Contents Association
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• v.16 no.10
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• pp.393-402
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• 2016

To compensate for limited the satisfaction survey currently conducted by Korea Metrological Administration (KMA), a sentiment analysis via a social networking service (SNS) can be utilized. From 2011 to 2014, with the sentiment analysis, Twitter who had commented 'KMA' had collected, then, using $Na{\ddot{i}}ve$ Bayes classification, we were classified into three sentiments: positive, negative, and neutral sentiments. An additional dictionary was made with morphemes appeared only in the positive, negative, and neutral sentiments of basic $Na{\ddot{i}}ve$ Bayes classification, thus the accuracy of sentiment analysis was improved. As a result, when sentiments were classified with a basic $Na{\ddot{i}}ve$ Bayes classification, the training data were reproduced about 75% accuracy rate. Whereas, when classifying with the additional dictionary, it showed 97% accuracy rate. When using the additional dictionary, sentiments of verification data was classified with about 75% accuracy rate. Lower classification accuracy rate would be improved by not only a qualified dictionary that has increased amount of training data, including diverse keywords related to weather, but continuous update of the dictionary. Meanwhile, contrary to the sentiment analysis based on dictionary definition of individual vocabulary, if sentiments are classified into meaning of sentence, increased rate of negative sentiment and change in satisfaction could be explained. Therefore, the sentiment analysis via SNS would be considered as useful tool for complementing surveys in the future.

• The Journal of the Korea Contents Association
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• v.12 no.11
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• pp.30-38
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• 2012

Sentiment analysis is concerned with extracting and analyzing different kinds of user sentiment expressed in a variety of social media such as blog and twitter. Although sentiment analysis techniques are actively studied for these days, evaluation sets are not developed yet for Korean sentiment analysis. In this paper, we constructed an evaluation set for Korean sentiment analysis. To evaluate sentiment analysis systems more throughly, each sentence in our evaluation set is tagged with the polarity of the sentiment as well as the category and the strength of the sentiment. We divide kinds of sentiment into 7 positive categories and 15 negative categories. Each category is given the strength of the sentiment from 1 to 3. Our evaluation set consists of 3,270 sentences extracted from various social media. For each sentence, 5 human taggers assigned the category and the strength of the sentiment expressed in the sentence. The ratio of inter-taggers agreement was 93% in the polarity, 70% in the category, 58% in the strength of sentiment. The ratio of inter-taggers agreement our evaluation set is a bit higher than other evaluation sets developed for German and Spanish. This result shows our evaluation set can be used as a reliable resource for the evaluation of sentiment analysis systems.

• IE interfaces
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• v.12 no.2
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• pp.247-253
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• 1999

The main objective of this study is to quantify the appropriateness of the sensibility vocabularies used in sensibility ergonomic evaluation scheme by applying structural equation model. In the conventional sensibility ergonomic evaluation scheme, factor analysis is employed to classify various vocabularies into some common factors. However, since the vocabularies were chosen quite subjectively, it is difficult to ascertain that they represent the product attributes properly. It was shown in a case study that the structural equation model provides the quantitative results to verify whether the selected vocabularies are eligible for further steps of sensibility ergonomic evaluation.

• Journal of Korean Society for Quality Management
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• v.25 no.2
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• pp.154-168
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• 1997

This paper considers an a, pp.ication of one of the sensory engineering's techniques, extraction and categorization of the sensory words, to the product of cars. The fourty five (45) sensory words are extracted in three steps. Two groups, which are characterized by whether possessing a car or not and each group consisting of one hundred persons randomly selected from the twenties or thirties, are asked to answer the questionaires with the extracted words in the five-grade semantic differential. The factor analysis is used to categorize the extracted sensory words, and shows that the words can be grouped into four categories.

• Science of Emotion and Sensibility
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• v.9 no.2
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• pp.119-132
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• 2006

The dimensions of affection structure from hand movements was developed for the purpose of understanding relationship between affective words and physical factors to apply it to computing environment. To analyze hand movements, three dimensions -direction, time, weight- were found through reconstructing sub-properties of Laban Movement Analysis. The direction dimension has five freedoms of movement (horizontal, vertical, sagittal, circular, shaking) while the time and weight dimensions both have two sub categories each, (sudden, sustained), (light, strong) respectively. By factorial design using the three dimensions, twenty movement were videotaped. Participants rated a list of fifty korean affective words on each twenty movements. The results were studied by nonlinear principal component analysis. The results suggested that time and weight dimensions are closely related with arousal level dimension of affection. Strong and sudden movements associated with highly aroused affection, while light and sustained movements associated with the opposite affection. The direction sub-dimensions were found to be associated with the kinds of affection. Linear movements like horizontal, vortical and sagittal direction were correlated to highly aroused negative affection. Circular movements were found to correlate closely by fun and delight on the graph, while shaking movements were correlated to anxiety and impatience. These results imply that the dimensions of affection structure and sub-properties of hand movements are closely connected with each other.

• Science of Emotion and Sensibility
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• v.19 no.4
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• pp.13-20
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• 2016

Recently, life-logging service which has expanded to measure and record the daily life of the users and to share with others are increasing. In particular, as life-logging services based on the application has become popular with the development of wearable-devices and smart-phones, the contents of this service are produced by user behavior and are provided in infographic menu form. The purpose of this paper is to extract user behavior and classify for making contents items of life-logging service. For this paper, the first of all, we discuss the definition and characteristics of life-logging and research the contents based on user behavior related to life-logging by the publications including thesis, articles, and books. Secondly, we extract and classify the user behavior to build the contents for life-logging service. We gather users' action words from publication materials, researches, and contents of existing life-logging service. And then collected words are analyzed by FGI (Focus Group Interview) and survey. As the result, 39 words which suit for contents of life-logging service are extracted by verify suitability. Finally, the extracted 39 words are classified for 19 categories -'Eat', 'Keep house', 'Diet', 'Travel', 'Work out', 'Transit', 'Shoot', 'Meet', 'Feel', 'Talk', 'Care for', 'Drive', 'Listen', 'Go online', 'Sleep', 'Go', 'Work', 'Learn', 'Watch' - which are suggested by the surveys, statistical analysis, and FGI. We will discuss the role and limitations of this results to build contents configuration based on life-logging application in this study.

• Journal of Intelligence and Information Systems
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• v.19 no.1
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• pp.95-110
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• 2013

Recently, the amount of unstructured data being generated through a variety of social media has been increasing rapidly, resulting in the increasing need to collect, store, search for, analyze, and visualize this data. This kind of data cannot be handled appropriately by using the traditional methodologies usually used for analyzing structured data because of its vast volume and unstructured nature. In this situation, many attempts are being made to analyze unstructured data such as text files and log files through various commercial or noncommercial analytical tools. Among the various contemporary issues dealt with in the literature of unstructured text data analysis, the concepts and techniques of opinion mining have been attracting much attention from pioneer researchers and business practitioners. Opinion mining or sentiment analysis refers to a series of processes that analyze participants' opinions, sentiments, evaluations, attitudes, and emotions about selected products, services, organizations, social issues, and so on. In other words, many attempts based on various opinion mining techniques are being made to resolve complicated issues that could not have otherwise been solved by existing traditional approaches. One of the most representative attempts using the opinion mining technique may be the recent research that proposed an intelligent model for predicting the direction of the stock index. This model works mainly on the basis of opinions extracted from an overwhelming number of economic news repots. News content published on various media is obviously a traditional example of unstructured text data. Every day, a large volume of new content is created, digitalized, and subsequently distributed to us via online or offline channels. Many studies have revealed that we make better decisions on political, economic, and social issues by analyzing news and other related information. In this sense, we expect to predict the fluctuation of stock markets partly by analyzing the relationship between economic news reports and the pattern of stock prices. So far, in the literature on opinion mining, most studies including ours have utilized a sentiment dictionary to elicit sentiment polarity or sentiment value from a large number of documents. A sentiment dictionary consists of pairs of selected words and their sentiment values. Sentiment classifiers refer to the dictionary to formulate the sentiment polarity of words, sentences in a document, and the whole document. However, most traditional approaches have common limitations in that they do not consider the flexibility of sentiment polarity, that is, the sentiment polarity or sentiment value of a word is fixed and cannot be changed in a traditional sentiment dictionary. In the real world, however, the sentiment polarity of a word can vary depending on the time, situation, and purpose of the analysis. It can also be contradictory in nature. The flexibility of sentiment polarity motivated us to conduct this study. In this paper, we have stated that sentiment polarity should be assigned, not merely on the basis of the inherent meaning of a word but on the basis of its ad hoc meaning within a particular context. To implement our idea, we presented an intelligent investment decision-support model based on opinion mining that performs the scrapping and parsing of massive volumes of economic news on the web, tags sentiment words, classifies sentiment polarity of the news, and finally predicts the direction of the next day's stock index. In addition, we applied a domain-specific sentiment dictionary instead of a general purpose one to classify each piece of news as either positive or negative. For the purpose of performance evaluation, we performed intensive experiments and investigated the prediction accuracy of our model. For the experiments to predict the direction of the stock index, we gathered and analyzed 1,072 articles about stock markets published by "M" and "E" media between July 2011 and September 2011.

• Archives of design research
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• v.17 no.4
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• pp.141-148
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• 2004

The purpose of this study is to define the emotion that expressed in step animation and to quantify the intuitional expression of emotion that related step for using extract, measure, analysis the stimulate element about step. The survey of relation with 27 word of emotional expressions and 36 moving pictures of step sample is used for method of this test. The emotional mental structure is transferred to 2 dimensional planes as applying the results of analysis of integrated data using Quantification Method 3, which the integrated data is composed two axial - confidential axial and stabling axial. Analysis of distribution of 2 dimensional diagram shows that the second of the plane and the third of the plane have much data. However, the first of the plane and the forth of the plane have a little data. Through this kind of analysis of graph, it is difficult to express a different emotion between unstable the timidity mind and stable feel the timidity mind using only step analysis. Six difference types about physical elements affecting to emotion are selected and analyzed such as the paces of step, the rate of step, the movement angle of pelvis, the swing range of arm, angle of backbone and the lean angle of body. The result is that the rate of stop and the lean angle of body are the major element that effects to emotional stimulate of stop. This thesis argues about methods transforming subjective expression to objective and quantitative expression with the state of delicate emotion of character apply to step animation naturally. Those data to apply to multi-contents in future are the main target in this study.

• 한국HCI학회:학술대회논문집
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• 2006.02b
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• pp.258-266
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• 2006

시대의 흐름에 따라 문화적 차이를 극복한 전략적인 제품 디자인의 중요성이 커지고 있다. 이에 따라, 문화의 성향을 파악하여 적절하게 대응할 수 있는 디자인이 필요하지만, 지금까지는 제품에 대한 선호도 또는 감성어휘 중심의 설문조사를 통해 각 문화의 통계적인 경향성을 파악하는 것이 대부분이었다. 그러나 디자인의 선호에 차이를 발생시키는 근본적인 문화 배경적 원인을 파악하지 않으면 체계적이고 지속적인 디자인 전략의 수립이 어렵다. 본 연구는 상이한 문화권에서 발생하는 제품디자인 선호 차이에 대한 원인을 문화적 성향의 차이에서 찾으려고 하였다. 또, 문화적 성향이 제품의 선호에 미치게 되는 원인을 문화연구 방법의 하나인 기호학을 통해 분석하고, 그 관계를 체계적인 모델로 설명하고자 하였다. 이를 위해 한국과 프랑스, 두 문화권에서 웹 기반 설문조사를 실시하여 문화적 성향과 모바일 폰 이라는 제품에 대한 기본적 개념을 파악하고 선호하는 디자인을 조사하였다. 그 결과 첫째, 문화적 성향이 모바일 폰의 개념 형성에 영향을 미쳐 한국에서는 필수품이자 자신을 표현하는 제품으로, 프랑스에서는 필수적이지 않으며 개인에게 유용한 도구로 여기며 그에 따라 한국에서는 디자인을, 프랑스에서는 기능적 요소를 중요하게 생각하는 등의 차이가 발생하는 것을 발견하였다. 또, 상이한 제품개념이 디자인 선호에 차이를 유발하여 프랑스에서는 유(柔)하고 정적인 디자인을, 한국에서는 강하고 동적인 감성의 디자인을 선호함을 분석할 수 있었다. 더 나아가 이러한 결과를 종합하여 기호학적 개념에 입각하여 체계적인 모델을 제안함으로써 상이한 문화에서의 상이한 디자인 선호에 대한 원인을 규명할 수 있었다.