• 한국의류학회지
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• 제33권11호
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• pp.1817-1827
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• 2009

This study analyzes how the purchase reviews of fashion merchandise influence consumer trust, satisfaction, commitment, word-of-mouth intention, and repurchase intention in internet shopping malls. The survey was conducted from October $15^{th}$ to December $5^{th}$ in 2008, and 368 responses were used in the data analysis. The statistical analysis methods were frequency analysis, factor analysis, reliability analysis, and multiple regression analysis. The results show that the purchase reviews factors of fashion merchandise in internet shopping malls were amusement, assentation, overstatement, genuineness, and usefulness. The assentation, genuineness, and usefulness of purchase reviews have an effect on consumer trust and satisfaction. The amusement, overstatement, and usefulness of purchase reviews have an effect on the emotional commitment of consumers, while the amusement, assentation, overstatement, genuineness, and usefulness of purchase reviews influence the reasonable commitment of consumers. Consumer trust and commitment effect word-of-mouth intention and repurchase intention in internet shopping malls.

• 대한간호학회지
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• 제29권4호
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• pp.755-765
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• 1999

Most people experience fatigue at some point in their lives, and they say the word ‘fatigue’ in their ordinary conversational speech. The ordinary word is used as a military or engineering term and has been studied in various different disciplines, such as ergonomics, physiology, psychology, medicine, and nursing. In spite of its widespread uses, however, fatigue has not been well defined. The term of fatigue Is thus often used with different meanings and is applied in diverse contexts that had led to a confusion of ideas. In people with cancer, fatigue is reported as a major distress. Despite the importance of fatigue in cancer patients, the phenomena of fatigue is poorly understood. Therefore, the purpose of the present study is to analyze the concept of fatigue in people with cancer. The process for the concept analysis was guided by Walker and Avant's conceptual analysis methodology. The identified attributes of fatigue in the present study were subjective feeling, lack of energy, sustenance, and multidimensions. The antecedents were cancer treatment and economic status. The consequences were decreased daily, vocational, leisure, and social activities, uncertainty, and difficulties in adjustment. Symptoms (pain, anorexia, and insomnia) and emotional disturbance were not clear whether they are antecedents or consequences. However, they are related with cancer related fatigue. Even though still in the beginning stage, instruments measuring cancer related fatigue have been developed by some nursing investigators.

• 인터넷정보학회논문지
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• 제10권6호
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• pp.113-121
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• 2009

본 논문에서는 지역적으로 서로 다른 감성을 지닌 영상을 검출하기 위해서 감성 스케치를 이용한 영상 검색 시스템을 제안 하였다. 제안하는 검색 시스템은 영상을 $17{\times}17$의 겹치지 않는 부분영역으로 나누고, 각 부분영역에 대한 감성 특징을 추출한다. 본 논문에서는 부분영역 내에서 감성 특징을 추출하기 위해서, H. Nagumo의 배색이미지차트에서 제안하는 160개 감성어에 대한 감성 색상을 이용하였다. 부분영역으로부터 해당 감성어에 대한 감성 색상의 분포정도를 계산하여 각 부분영역의 감성어에 대한 히스토그램 값 중 가장 큰 값을 지닌 감성어를 취하게 된다. 제안하는 감성 스케치를 이용한 영상 검색 시스템은 Corel 영상 데이터베이스에 대해서 유효성을 평가하여, 전역적 방법보다 우수한 검색 정확도와 재현도를 가짐을 보여주었다.

• International Journal of Computer Science & Network Security
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• 제21권8호
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• pp.238-246
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• 2021

The rapid rise of the Internet and social media has resulted in a large number of text-based reviews being placed on sites such as social media. In the age of social media, utilizing machine learning technologies to analyze the emotional context of comments aids in the understanding of QoS for any product or service. The classification and analysis of user reviews aids in the improvement of QoS. (Quality of Services). Machine Learning algorithms have evolved into a powerful tool for analyzing user sentiment. Unlike traditional categorization models, which are based on a set of rules. In sentiment categorization, Bidirectional Long Short-Term Memory (BiLSTM) has shown significant results, and Convolution Neural Network (CNN) has shown promising results. Using convolutions and pooling layers, CNN can successfully extract local information. BiLSTM uses dual LSTM orientations to increase the amount of background knowledge available to deep learning models. The suggested hybrid model combines the benefits of these two deep learning-based algorithms. The data source for analysis and classification was user reviews of Indian Railway Services on Twitter. The suggested hybrid model uses the Keras Embedding technique as an input source. The suggested model takes in data and generates lower-dimensional characteristics that result in a categorization result. The suggested hybrid model's performance was compared using Keras and Word2Vec, and the proposed model showed a significant improvement in response with an accuracy of 95.19 percent.

• The Journal of Asian Finance, Economics and Business
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• 제8권7호
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• pp.579-589
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• 2021

In the era of tough competition, the customer's emotional attachment to brand plays a vital role to the successes and failures of enterprises. Specifically in the case of doing business online, brands have to cope with the troubles of rising from brand hate as brand avoidance, negative word of mouth and brand retaliation. Traditionally, the brand communication is very hard to control and with online communities, the problems tend to be even more severe. This paper aims to explore and discuss the core concept, the driven factors and the actionable consequences of brand hate among netizens. A total of 358 valid responses were obtained from surveys taken from the internet users across the nation. Partial Least Square - Structural Equation Modeling (PLS-SEM) was conducted using Smart PLS to assess the hypotheses. The result shows that the expression of brand hate among netizen consists of active hate and passive hate. Deficit value, deceptive advertising, negative past experience and ideology incompatibility have been confirmed as influencing factors on customers' brand hate emotion. Then brand hate itself causes the customer's actionable outcomes such as brand avoidance, brand negative word of mouth and brand retaliation. Along with the theoretical contributions and managerial implications have been recommended for enterprises to avoid netizens' brand hate.

• 한국산학기술학회논문지
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• 제22권3호
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• pp.460-469
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• 2021

많은 현대인들은 질병, 일상생활, 직장, 환경오염 등의 원인으로 스트레스에 시달리게 되면서 일상으로부터 벗어나 신체적, 정신적 여유를 누리는 보다 편안하고 안정된 삶을 원하고 있다. 이러한 삶을 원하는 사람들이 증가하게 되면서 사회적으로 웰빙, 웰니스와 같은 용어는 보편화되고 관련 산업도 발전하고 있다. 웰니스 산업 중 웰니스 엔터테인먼트 콘텐츠 산업은 가장 높은 성장세를 보이고 있는 영역 가운데 하나로, 본 연구는 온라인 매체를 통해 제공되는 웰니스 콘텐츠가 어떠한 과정을 통해 이용자의 심리적 웰빙 수준을 향상시키는 지를 텔레프레젠스의 매개효과를 통해 살펴보고자 한다. 구체적으로 본 연구는 온라인 웰니스 엔터테인먼트 콘텐츠의 감각, 감정, 인지속성이 텔레프레젠스를 통해 심리적 웰빙과 구전효과에 미치는 영향관계를 연구모형으로 제시한다. 305명을 대상으로 웰니스 콘텐츠로써의 명상 앱 체험 경험에 대한 설문조사 데이터를 실증 분석한 결과 연구모형이 가정한 가설이 채택됨을 증명할 수 있었다. 본 연구결과는 웰니스 콘텐츠가 이용자의 텔레프레젠스와 구전효과를 유도함을 보여줌으로써 향후 단순한 심신안정용에만 한정되기보다 향후 수익모델로 발전시키기 위한 방안이 필요함을 시사한다.

• 디지털융복합연구
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• 제10권10호
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• pp.475-482
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• 2012

지방자치시대에 모든 지방자치단체들은 본인들의 지방정부를 좋은 이미지로 알려 관광이나 경제통상에 이득이 되도록 노력하고 있기 때문에 지역이미지가 조각된 홍보영상은 중요하고 필요하다. 따라서 본 연구는 지역이미지와 시정홍보영상 이미지간의 관계를 알아보고 효과적인 시정홍보영상제작을 위한 기초자료를 제공하고자 한다. 평소 지역에 대해 가지고 있는 이미지를 감성어휘로 추출하여 시정홍보영상 이미지에도 동일한 감성어휘가 들어가 있는지와 홍보영상이미지에서의 이미지 어휘에 대한 평균값이 상승 혹은 하락을 하였는지를 조사하여 지역이미지가 긍정적으로 투영된 시정홍보영상 이미지 제작을 해야 한다는 것을 알 수 있었다.

• 한국초등과학교육학회지:초등과학교육
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• 제39권2호
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• pp.255-267
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• 2020

Students' engagement is important for meaningful learning and it has multifaceted aspects for their science learning. This study investigated elementary students' perceptions of science learning engagement. The subjects of this study were 341 4^th to 6^th elementary students. The survey questionnaires were 5-Likert scale questions and free response questions on science learning engagement. The results showed that elementary students' perceptions of behavioral engagement were higher than emotional and cognitive engagement. Keyword network analysis with NetMiner program showed that the frequent key words of science learning engagement were 'experiment', 'listening', and 'teachers' explanation', which were mostly the behavioral types of engagement. The degree centrality and eigenvector centrality of these key words appeared high. 'Interest', which is emotional engagement, were also one of the frequent key words, but the centralities of this word were relatively low. The Frequent key words of science learning disengagement were mostly related with off-tasks, not doing expected behaviors and negative emotions about science and science learning. Educational implications on science learning engagement were discussed.

• 대한인간공학회지
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• 제26권3호
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• pp.17-25
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• 2007

'Emotional value' has been a buzz word for design and ergonomics in the era of business innovation. However, the complication of 'emotion' in terms of literal and practical meaning has made it a challenging but confusing task for designers to develop a new product with emotional value. 'Sensibility' and 'emotion' are interchangeable terms to describe human feeling ('gamsung' in Korean). The confusion reached at its peak with Korean terms. Even scholars in Korean language, psychologists, ergonomists, and designers are bewildered at the choice of proper expression for human feeling in both Korean and English. The difficulty could explain the problems in 'sensibility ergonomics' in Korea. The purpose of this paper is to provide both fundamental and satisfying information with people in the area of 'sensibility ergonomics'. Therefore, in this paper, a number of articles and books on sensibility, psychology, sensibility ergonomics, and design were reviewed to clarify the meaning of sensibility and relationship among similar words that have been used with unintentional misunderstanding. Also many adjectives on human sensibility were collected and complied for the use of sensibility evaluation.

• 문화기술의 융합
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• 제6권2호
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• pp.561-566
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• 2020

본 논문은 우울증 진단 환자의 증상 완화를 위한 참참참 놀이 및 끝말잇기 놀이 로봇을 설계 및 구현한다. 우울증의 핵심 증상은 삶에 대한 흥미와 관심을 상실하는 것으로, 우울증 진단 환자가 로봇을 통해 자신의 표정에 드러나는 감정 분석을 확인하고 참참참 혹은 끝말잇기 놀이를 진행한다. 놀이 후 표정에 드러나는 감정을 다시 분석하여 보고 받음으로 구현 로봇의 기능을 확인한다. 간단한 놀이를 통해 우울증을 진단 받은 환자의 질환이 완벽하게 치료될 수는 없지만, 점진적인 활용을 통해 증상 완화에 기여할 수 있다. 참참참, 끝말잇기 놀이 로봇의 설계는 Thecorpora사의 상호작용이 가능한 오픈소스형 로봇 Q.bo One를 사용한다. Q.bo One의 시스템은 사용자의 얼굴을 캡쳐하여 사진을 촬영하고, Azure 서버에 값을 전달하여 축적된 데이터를 통해 놀이 전 후의 감정 분석을 확인한다. 놀이는 Q.bo One의 OS인 라즈비안에서 프로그래밍 언어 Python을 활용하여 구현하고 외부센서들과 상호작용하여 작동하도록 구현한다. 본 논문은 놀이 로봇으로 비교적 짧은 시간에 우울증 진단 환자의 증상 완화에 도움을 주는 것을 목적으로 한다.