• 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.

• Proceedings of the Korean Society for Emotion and Sensibility Conference
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• 2003.05a
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• pp.141-147
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• 2003

본 연구의 목적은 사용성과 평가에 기초하여 사용성과 착용성 평가에 기초하여 웨어러블 컴퓨터의 디자인 프로토타입을 개발하는 것으로서, 실증적 자료를 토대로 하여 웨어러블 컴퓨터의 디자인 적합성 및 물리적 인터페이스 속성을 개선하는데 목표를 두었다. 본 연구에서는 이를 위하여 웨어러블 컴퓨터에 디자인 시안 1종을 실물로 제작하고 컴퓨팅에 능숙한 일반 사용자 10명과 택배직에 종사하는 전문 사용자10명을 대상으로 디자인 시안을 사용하게 한 후, 디자인 시안의 사용성과 착용성을 평가하기 위한 심층면접을 실시하였으며, 그 결과 도출된 문제점을 실증적으로 분석하였다. ‘외관’, ‘관리의 용이성’, ‘컴퓨팅 기기 위치의 적절성’, ‘와이어 경로의 적절성’, ‘조작의 용이성’, ‘위험성’, ‘유용성’, ‘인지적 변화’, 의 9가지 항목별로 정성적, 정량적 분석결과를 도출하였으며, 이러한 결과를 기반으로 디자인 시안의 세부적인 디자인 수정안을 도출하였으며, 사용성과 착용성 평가를 바탕으로 한 현재의 기술을 통해 구현 가능한 웨어러블 컴퓨터의 디자인 프로토타입의 기본형을 그래픽 시뮬레이션으로 제시하였다.

• Journal of the Korea Convergence Society
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• v.12 no.7
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• pp.193-205
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• 2021

The AI speaker market is growing steadily. However, the satisfaction of actual users is only 42%. Therefore, in this paper, we collected reviews on Amazon Echo Dot 3rd and 4th generation models to analyze what hinders the user experience through the topic changes and emotional changes of each generation of AI speakers. By using topic modeling analysis techniques, we found changes in topics and topics that make up reviews for each generation, and examined how user sentiment on topics changed according to generation through deep learning-based sentiment analysis. As a result of topic modeling, five topics were derived for each generation. In the case of the 3rd generation, the topic representing general features of the speaker acted as a positive factor for the product, while user convenience features acted as negative factor. Conversely, in the 4^th generation, general features were negatively, and convenience features were positively derived. This analysis is significant in that it can present analysis results that take into account not only lexical features but also contextual features of the entire sentence in terms of methodology.

• Journal of Intelligence and Information Systems
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• v.27 no.2
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• pp.55-78
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• 2021

Tosolve complex and diverse social problems and ensure the quality of life of individuals, social robots that can interact with humans are attracting attention. In the past, robots were recognized as beings that provide labor force as they put into industrial sites on behalf of humans. However, the concept of today's robot has been extended to social robots that coexist with humans and enable social interaction with the advent of Smart technology, which is considered an important driver in most industries. Specifically, there are service robots that respond to customers, the robots that have the purpose of edutainment, and the emotionalrobots that can interact with humans intimately. However, popularization of robots is not felt despite the current information environment in the modern ICT service environment and the 4th industrial revolution. Considering social interaction with users which is an important function of social robots, not only the technology of the robots but also other factors should be considered. The design elements of the robot are more important than other factors tomake consumers purchase essentially a social robot. In fact, existing studies on social robots are at the level of proposing "robot development methodology" or testing the effects provided by social robots to users in pieces. On the other hand, consumer emotions felt from the robot's appearance has an important influence in the process of forming user's perception, reasoning, evaluation and expectation. Furthermore, it can affect attitude toward robots and good feeling and performance reasoning, etc. Therefore, this study aims to verify the effect of appearance of social robot and consumer emotions on consumer's attitude toward social robot. At this time, a social robot design evaluation model is constructed by combining heterogeneous data from different sources. Specifically, the three quantitative indicator data for the appearance of social robots from the ABOT Database is included in the model. The consumer emotions of social robot design has been collected through (1) the existing design evaluation literature and (2) online buzzsuch as product reviews and blogs, (3) qualitative interviews for social robot design. Later, we collected the score of consumer emotions and attitudes toward various social robots through a large-scale consumer survey. First, we have derived the six major dimensions of consumer emotions for 23 pieces of detailed emotions through dimension reduction methodology. Then, statistical analysis was performed to verify the effect of derived consumer emotionson attitude toward social robots. Finally, the moderated regression analysis was performed to verify the effect of quantitatively collected indicators of social robot appearance on the relationship between consumer emotions and attitudes toward social robots. Interestingly, several significant moderation effects were identified, these effects are visualized with two-way interaction effect to interpret them from multidisciplinary perspectives. This study has theoretical contributions from the perspective of empirically verifying all stages from technical properties to consumer's emotion and attitudes toward social robots by linking the data from heterogeneous sources. It has practical significance that the result helps to develop the design guidelines based on consumer emotions in the design stage of social robot development.

• Smart Media Journal
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• v.10 no.1
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• pp.116-123
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• 2021

Due to the rapid growth of the online fashion market and the resulting expansion of online choices, there is a problem that the seller cannot directly respond to a large number of consumers individually, although consumers are increasingly demanding for more personalized recommendation services. Images are being tagged as a way to meet consumer's personalization needs, but when people tagging, tagging is very subjective for each person, and artificial intelligence tagging has very limited words and does not meet the needs of users. To solve this problem, we designed an algorithm that recognizes the shape, attribute, and emotional information of the product included in the image with AI, and codes this information to represent all the information that the image has with a combination of codes. Through this algorithm, it became possible by acquiring a variety of information possessed by the image in real time, such as the sensibility of the fashion image and the TPO information expressed by the fashion image, which was not possible until now. Based on this information, it is possible to go beyond the stage of analyzing the tastes of consumers and make hyper-personalized clothing recommendations that combine the tastes of consumers with information about trends and TPOs.

• Journal of Information Technology and Architecture
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• v.11 no.3
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• pp.347-357
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• 2014

This research aims to suggest the possibility of functional culture contents based on interdisciplinary methodologies, especially for people who have Autism Spectrum Conditions, or those who have disabilities on express and receive gamsung (emotions). Recently, the development of application technologies in smartphones and tablet computers needs of functional culture contents, which are connected with the gamsung system. Moreover, the potential of marketplace of functional culture contents is emerging, as can be seen from the success of Augmentative and Alternative Communications (AAC) applications. Therefore, with the development of more applications that prevent and resolve Gamsung Disabilities anticipatively, there will be a positive economic effect of reducing back on intervention expenses as well as the construction of new contents ecosystem. So, in this research, we will attempt to make an approach of using the cultural semiotics methodology in finding attributes and features of applications that help to keep mental stability and balance for people with gamsung Disabilities. Particularly, this research will suggest an interdisciplinary theory on healing contents making methodology, using contents analysis; user interface (UI) analysis; and user experience (UX) analysis on existing smart healing applications.

• Journal of Digital Convergence
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• v.19 no.7
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• pp.79-85
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• 2021

After COVID-19, the number of individuals participating in delivery platforms has increased. They are using the participation of the delivery platform as a means of creating a new source of income as well as a means of sports and hobbies. This phenomenon is related to a social phenomenon called 'N-jober'. However, there are still few studies examining this phenomenon. Therefore, this study intends to examine the phenomenon of individual participation in delivery platforms and their issues. Text mining was performed on news data from January 2019, when COVID-19 started. As a result, social issues related to the increase in individual participation in delivery platforms were derived into 5 topics(Introduction to the Phenomenon, Characteristics of Participants, Participant's Income and Fees, Characteristics as a Job, Concern about Potential Risks). This study has significance in that it expanded the perspective of academic discussion on delivery platform business to individual participants.

• Information Systems Review
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• v.25 no.1
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• pp.27-46
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• 2023

Research on restaurant recommender systems has been proposed due to the development of the food service industry and the increasing demand for restaurants. Existing restaurant recommendation studies extracted consumer preference information through quantitative information or online review sensitivity analysis, but there is a limitation that it cannot reflect consumer semantic preference information. In addition, there is a lack of recommendation research that reflects the detailed attributes of restaurants. To solve this problem, this study proposed a model that can learn the interaction between consumer preferences and restaurant attributes by applying deep learning techniques. First, the convolutional neural network was applied to online reviews to extract semantic preference information from consumers, and embedded techniques were applied to restaurant information to extract detailed attributes of restaurants. Finally, the interaction between consumer preference and restaurant attributes was learned through the element-wise products to predict the consumer preference rating. Experiments using an online review of Yelp.com to evaluate the performance of the proposed model in this study confirmed that the proposed model in this study showed excellent recommendation performance. By proposing a customized restaurant recommendation system using big data from the restaurant industry, this study expects to provide various academic and practical implications.

• Journal of the Korean Society of Clothing and Textiles
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• v.42 no.3
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• pp.428-437
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• 2018

This study derives evaluation terms by analyzing the semantic relationship between design elements and sentiment terms in regards to fashion design. As for research methods, a total of 38,225 texts from Daum and Naver Blogs from November 2015 to October 2016 were collected to analyze the parts, frequency, centrality and semantic networks of the terms. As a result, design elements were derived in the form of a noun while fashion image and user's emotional responses were derived in the form of adjectives. The study selected 15 noun terms and 52 adjective terms as evaluation terms for men's striped shirts. The results of semantic network analysis also showed that the main contents of the users of men's striped shirts were derived as characteristics of expression, daily wear, formation, and function. In addition, design elements such as pattern, color, coordination, style, and fit were classified with evaluation results such as wide, bright, trendy, casual, and slim.

• The Journal of the Korea Contents Association
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• v.20 no.8
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• pp.315-326
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• 2020

Corporate efforts to build strong brands have made consumers interested in brand love. In the field of brand love, however, there is a lack of systematic research on the multidimensionality of the concept of brand love and on the scale development to measure it. Thus, based on the methodological research design of Churchill(1979) and DeVellis(1991), this study explored properties of brand love and classified them into two levels - 'emotion' and 'relationship' - and generated corresponding measurement items. To do this, the research was conducted in a total of eight stages, including preliminary studies such as literature review, open surveys, and in-depth interviews, as well as the main study process in which the factors were analyzed step by step. As a result, the level of emotion appeared to have five subcomponents (self-esteem, warmth, interest, responsibility, pleasure) with 19 items, and the level of relationship - three subcomponents (unchanging, sharing/supporting, understanding) with 11 items, adding up to a total of 30 measurement items for brand love with reliability, convergent and discriminant validity, and nomological validity. Additionally, we intended to expand the scope of research related to brand love by presenting the result model of organic interaction between the concepts that constitute brand love and proposing '4 categories of brand love strength' based on it.