• Science of Emotion and Sensibility
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• v.12 no.1
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• pp.87-96
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• 2009

Recently, there is a tendency of consumer's participation gradually increasing in the design shaping process. Consumers make evaluation or suggestion about the shape of the product, and the industries lay out schemes to elicit consumers' participation. However, when it comes to dealing with the shape of the product, consumer and designer has a fundamental difference in their point of view, and it works as interruption to the efficient communication between the consumer and designer. Therefore, this study will examine the difference of consumer's and designer's view of products' shape, and the guidelines of effective molding which elicit the consumers' affective responses. First, I established the sensible image vocabulary based on the shape of the product. And based on the vocabulary, I carried out the same experiments to the consumers and designers. As a result, the affective responses of the two groups toward the shape have similar characteristics and designers' reactions found out to be more dramatic than consumers.

• The Journal of the Korea Contents Association
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• v.17 no.1
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• pp.183-192
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• 2017

This study aims to suggest improved design for both non-smokers and smokers to minimize inconvenience of smoke, at the same time, allow smoking in comfortable environment. The study was researched in three categories: First, consciousness research regarding smoking booth, second, preference research regarding product design, and third, research on emotional words about smoking booth by emotion evaluation. The result of design preference research was, first of all, smoking booth for smokers should be designed in both notable and familiar shape rather than stiff and rough shape. Second, color for the booth should apply warm colors such as white, pastel, and bright tone rather than prime colors. Third, the internal circulation filter in smoking booth should be managed thoroughly. In addition, extra seats and ventilation design is necessary to prevent passive smoking. The result of emotion evaluation was that people recognized certain words in four aspects. Each image word for factor 1 was "functional emotion', factor 2 was "psychological emotion", factor 3 as "color emotion", and factor 4 as "shape emotion". User-centered service design is necessary for both smokers and non-smokers, to minimize the damage by smoke and to spend time for short break.

• Science of Emotion and Sensibility
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• v.11 no.3
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• pp.375-385
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• 2008

This study intended to grasp image association on human's product and cognition response characteristic, and analyze their correlation with product preference. For this, photos of mobile phones and proposal-type products were selected for experiment stimuli, and an experiment expressing associated word and an experiment evaluating preference of each product's photo were made. With the experiments, two results were derived. First, in linguistic cognition response on product with use experience, application of emotional expression increased as the level of preference increased by mixing expressions of metaphor languages and emotional image. Second, non-use experience of product induces response corresponding to understanding on the object of cognition only perceptually and considering similarities with general experience information.

• Journal of the Korean Society for information Management
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• v.23 no.2
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• pp.167-183
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• 2006

This paper describes a metadata extraction technique based on natural language processing (NLP) which extracts personalized information from email communications between financial analysts and their clients. Personalized means connecting users with content in a personally meaningful way to create, grow, and retain online relationships. Personalization often results in the creation of user profiles that store individuals' preferences regarding goods or services offered by various e-commerce merchants. We developed an automatic metadata extraction system designed to process textual data such as emails, discussion group postings, or chat group transcriptions. The focus of this paper is the recognition of emotional contents such as mood and urgency, which are embedded in the business communications, as metadata.

• The Journal of the Korea institute of electronic communication sciences
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• v.18 no.4
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• pp.693-700
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• 2023

Sentiment analysis, a branch of natural language processing that classifies and identifies subjective opinions and emotions in text documents as positive or negative, can be used for various promotions and services through customer preference analysis. To this end, recent research has been conducted utilizing various techniques in machine learning and deep learning. In this study, we propose an optimal language model by comparing the accuracy of sentiment analysis for movie, product, and game reviews using existing RNN-based models and recent Transformer-based language models. In our experiments, LMKorBERT and GPT3 showed relatively good accuracy among the models pre-trained on the Korean corpus.

• Proceedings of the Korea Society of Design Studies Conference
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• 2004.10a
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• pp.196-197
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• 2004

• 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.

• Science of Emotion and Sensibility
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• v.12 no.1
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• pp.1-10
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• 2009

The purpose of this study is to find out the relationship between the design factor and the sensitivity in web site. The classification of sensitivity-types consists of the research of books and the survey, and the language specialist's review and the analysis of factor. The research of the Image Scale accomplished through the analysis of the result of sensitivity-types. The major findings of the analysis are summarized as follows. The webpage sensitivity-types are classified into the 7 types, namely 'refreshment', 'calm', 'refinement', 'strongness', 'youth', 'uniqueness', 'futurity'. As a result of analyzing of similarity between the adjectives by multiple standards, the web site Image Scale space consists of the axis between 'heavy-light' and 'soft-hard'. As a result of the research of relationship between the web site design factor and the emotion, the color and the layout influenced into 'soft-hard' much, and the light and the color influenced into 'heavy-light' much.

• Journal of the Korea Society of Computer and Information
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• v.19 no.12
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• pp.49-56
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• 2014

In this paper, we propose a method for identifying hidden principal sentiments among large scale texts from documents, social data, internet and blogs by analyzing standard language, slangs, argots, abbreviations and emoticons in those words. The IRLBA(Implicitly Restarted Lanczos Bidiagonalization Algorithm) is used for principal component analysis with large scale sparse matrix. The proposed system consists of data acquisition, message analysis, sentiment evaluation, sentiment analysis and integration and result visualization modules. The suggested approaches would help to improve the accuracy and expand the application scope of sentiment analysis in social data.

• Science of Emotion and Sensibility
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• v.17 no.4
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• pp.61-70
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• 2014

Verbal communication has limits in the interaction between robot and man, and therefore nonverbal communication is required for realizing smoother and more efficient communication and even the emotional expression of the robot. This study derived 7 pieces of nonverbal information based on shopping behavior using the robot designed to support shopping, selected facial expression as the element of the nonverbal information derived, and coded face components through 2D analysis. Also, this study analyzed the significance of the expression of nonverbal information using 3D animation that combines the codes of face components. The analysis showed that the proposed expression method for nonverbal information manifested high level of significance, suggesting the potential of this study as the base line data for the research on nonverbal information. However, the case of 'embarrassment' showed limits in applying the coded face components to shape and requires more systematic studies.