• The Journal of the Korea Contents Association
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• v.16 no.7
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• pp.112-121
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• 2016

The purpose of this research is to examine the effect of storytelling ads. To find out the effect, three different ads were created; one is no storytelling in ads, another is corporate storytelling ads, and the other is client storytelling ads. Each ads was exposed to high school students, and we analyzed their response to the ads such as ads recall, attitude toward ads, emotional response to ads, purchase intention, and the intention of word-of-mouth. The results showed that corporate storytelling ads among three ads was the most effective to recall the ads, and there was significant difference between corporate storytelling ads and no storytelling ads. In terms of attitude toward ads, there was significant difference between client storytelling and no storytelling ads. There were significant difference in positive emotion between client storytelling ads and no storytelling ads and between client storytelling ads and corporate storytelling ads, but no significant between corporate storytelling ads and no storytelling ads. Regarding emotion, students who were exposed to no storytelling ads showed the highest negative emotion, but the lowest negative emotion in client storytelling ads. There was significant difference in purchase intention between client storytelling and no storytelling ads and in the intention of word-of-mouth between corporate storytelling ads and no storytelling ads.

• Science of Emotion and Sensibility
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• v.20 no.1
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• pp.75-82
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• 2017

We propose a novel method for modeling emotional dimensions using expansion of Russell's (1980) emotional dimensions (Circumplex Model). The Circumplex Model represents emotional words in two axes (Arousal, Valence). However, other researchers have insisted that location of word in Russell's model which is expressed by single point could not represent exact position. Consequently, it is difficult to apply this model in engineering fields (such as Science of Emotion & Sensibility, Human-Computer-Interaction, Ergonomics, etc.). Therefore, we propose a new modeling method which expresses emotional word not as a single point but as a region. We conducted survey to obtain actual data and derived equations using ellipse formula to represent emotional region. Furthermore, we applied ANEW and IAPS which are commonly used in many studies to our emotional model using pattern recognition algorithm. Using our method, we could solve problems with Russell's model and our model is easily applicable to the field of engineering.

• Journal of the Ergonomics Society of Korea
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• v.30 no.1
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• pp.187-193
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• 2011

Objective: The aim of this study was to investigate the association between conceptual metaphors of affect and physical dimensions. Background: The evidence that affect is unconsciously linked to physical dimensions(e.g., position and color) has been obtained in western cultures. However, in eastern cultures, especially, in Korea, it has been seldom tested. It is indispensable to examine whether or not cultural differences exist for better understanding of the conceptual metaphors. Method: 50 positive and 50 negative words were adopted from previous studies in order to determine the relationship between physical domains and abstract affect. Three hypotheses were tested in this study: (1) Good is up. (2) Good is bright. (3) Good is right(for right-handers). The automatic association between valence(positive vs. negative) and vertical position (up vs. down) was investigated in experiment 1, in which 100 words were randomly presented on either the top or the bottom of a LCD screen and the evaluation time of the presented word was recorded. The unconscious association between valence and color(white and black) was examined in experiment 2, where each word was randomly presented in either white or black. Lastly, we tested whether right-handers tend to associate rightward space with positive ideas and leftward space with negative ideas. Results: Reaction time was faster when words were presented in metaphor congruent domains(e.g., 'positive words on the top, in bright color, and on right space vs. negative words on the bottom, in dark color, and on left region) than when they were shown in metaphor incongruent domains. Conclusion: The results might give the groundwork for various directions in further understanding perception, emotion, and behavior. Application: This study may provide useful points to GUI designers and service developers if further studies enhanced in validity and reliability are followed.

• Journal of the Korean BIBLIA Society for library and Information Science
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• v.25 no.3
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• pp.101-118
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• 2014

Given the context of rapid developing ubiquitous computing environment, it is imperative for users to search and use images based on affective meanings. However, it has been difficult to index affective meanings of image since emotions of image are substantially subjective and highly abstract. In addition, utilizing low level features of image for indexing affective meanings of image has been limited for high level concepts of image. To facilitate the access points of affective meanings of image, this study aims to utilize user-provided responses of images. For a data set, emotional words are collected and cleaned from twenty participants with a set of fifteen images, three images for each of basic emotions, love, sad, fear, anger, and happy. A total of 399 unique emotion words are revealed and 1,093 times appeared in this data set. Through co-word analysis and network analysis of emotional words from users' responses, this study demonstrates expanded word sets for five basic emotions. The expanded word sets are characterized with adjective expression and action/behavior expression.

• Korean Journal of Schizophrenia Research
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• v.17 no.1
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• pp.36-42
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• 2014

Objectives : The dysfunctional neural networks underlying self-evaluation in schizophrenia are overlapped with the neural structures involved in emotion regulation. The purpose of this study was to investigate the influence of anhedonia on the self-evaluation attitude of patients with schizophrenia. Methods : Twenty healthy controls and twenty patients with schizophrenia performed a self-evaluation task, presenting a pair of the face (self, familiar other, and unfamiliar other) and word (negative, neutral, and positive noun) at the same time. Participants were asked to evaluate relevance between the pairs by pressing a corresponding button. Relevance rating scores were compared between the groups and were correlated with the severity of physical and social anhedonia. Results : Patients evaluated the condition of a self face with a negative word and a familiar face with a negative word to be more relevant than healthy controls. In the patient group, the scores of relevance rating in the condition of an unfamiliar other face with a negative word were positively correlated with the anhedonia scale scores (physical : r=0.486, p=0.030 ; social : r=0.499, p=0.025). There was no correlation between the self-evaluation attitude and the severity of anhedonia. Conclusion : Patients with schizophrenia evaluate themselves badly in only negative circumstances, and anhedonia is not related to self-evaluation, but rather other-evaluation.

• Journal of the Korea Society of Computer and Information
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• v.28 no.10
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• pp.229-239
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• 2023

This study aims to explore the impact of algorithmic price discrimination on negative word-of-mouth (NWOM) through the lens of attribution theory. It also examines the mediating roles of intentional attributions and negative emotions, as well as the moderating effect of price sensitivity. For this study, 772 consumers who had purchased flight tickets completed a questionnaire survey, and the collected data were analyzed and tested using SPSS 27.0 and AMOS 24.0 software. The research findings reveal that algorithmic price discrimination has a significant positive impact on intentional attributions, negative emotions, and NWOM. Specifically, deliberate attributions and negative emotions mediate the relationship between algorithmic price discrimination and NWOM, while price sensitivity positively moderates the relationship between negative emotions and NWOM. Therefore, companies should consider disclosing algorithm details transparently in their marketing strategies to mitigate consumers' negative emotions and implement targeted strategies for consumers with different levels of price sensitivity to enhance positive word-of-mouth.

• Journal of the Korean Society for Library and Information Science
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• v.51 no.4
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• pp.121-138
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• 2017

As information users seek multimedia with a wide variety of information needs, information environments for multimedia have been developed drastically. More specifically, as seeking multimedia with emotional access points has been popular, the needs for indexing in terms of abstract concepts including emotions have grown. This study aims to analyze the index terms extracted from Getty Image Bank. Five basic emotion terms, which are sadness, love, horror, happiness, anger, were used when collected the indexing terms. A total 22,675 index terms were used for this study. The data are three sets; entire emotion, positive emotion, and negative emotion. For these three data sets, co-word occurrence matrices were created and visualized in weighted network with PNNC clusters. The entire emotion network demonstrates three clusters and 20 sub-clusters. On the other hand, positive emotion network and negative emotion network show 10 clusters, respectively. The results point out three elements for next generation of multimedia retrieval: (1) the analysis on index terms for emotions shown in people on image, (2) the relationship between connotative term and denotative term and possibility for inferring connotative terms from denotative terms using the relationship, and (3) the significance of thesaurus on connotative term in order to expand related terms or synonyms for better access points.

• The Journal of Economics, Marketing and Management
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• v.12 no.1
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• pp.65-75
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• 2024

Purpose: Through this study, first, we try to understand the characteristics of SNS beauty advertising using SNS. Second, focusing on S-O-R Theory, we aim to confirm the impact of SNS beauty advertising characteristics on positive emotions, commitment, and voluntary word-of-mouth intentions. Third, we intend to suggest measures related to effective SNS beauty advertising operation. Research design, data and methodology: To analyze the data collected of 308 questionnaires, the SPSS and AMOS statistical program was used, and the SNS beauty advertising characteristics were reclassified after analyzing the credibility and validity of the responses. Results: It was found that all SNS beauty advertising characteristics (interactivity, entertainment, credibility, and irritation) had a significant effect on positive emotions. However, entertainment and irritation did not have a significant effect on commitment. In addition, it was found that positive emotions had a positive effect on commitment, and commitment had a positive effect on voluntary word-of-mouth intentions, and positive emotions had no significant effect on voluntary word-of-mouth intentions. Conclusions: In order to improve consumers' commitment in SNS beauty advertising, it is important to secure trust through interaction, and it is judged that the more commit in SNS beauty advertising through positive emotions, the more spontaneous and positive word-of-mouth effect can be created.

• Asia pacific journal of information systems
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• v.25 no.4
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• pp.805-822
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• 2015

Online communities are an important source of electronic word-of-mouth (e-WOM). However, few studies have examined the use of such messages within the Middle Eastern context. This study focuses on Saudi women as members of an online beauty forum. Previous work suggested a mediating effect of gender, with women being more likely to trust word-of-mouth and follow it up with a purchase. A conceptual model with a theoretical underpinning from existing contributions in literature provides the basis of a coding framework for the message characteristics that influence members' e-WOM adoption. A total of 310 threads and 2200 messages coded into 5725 units were content analyzed to demonstrate cases where e-WOM was adopted and indicate further continuance intention with members returning to the forum. A new category of 'community bonding' was created from the content analysis given the prevalence of emotional aspects in messages. Emotion expressed in messages, often expressed in religious terms, is as influential and important as the cognitive aspects of community bonding.

• Proceedings of the Korea Information Processing Society Conference
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• 2021.11a
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• pp.760-763
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• 2021

텍스트를 자연어 처리를 위한 모델에 적용할 수 있게 언어적인 특성을 반영해서 단어를 수치화하는 방법 중 단어를 벡터로 표현하여 나타내는 워드 임베딩은 컴퓨터가 인간의 언어를 이해하고 분석 가능한 언어 모델의 필수 요소가 되었다. Word2vec 등 다양한 워드 임베딩 기법이 제안되었고 자연어를 처리할 때에 감성 분류는 중요한 요소이지만 다양한 임베딩 기법에 따른 감성 분류 모델에 대한 성능 비교 연구는 여전히 부족한 실정이다. 본 논문에서는 Emotion-stimulus 데이터를 활용하여 7가지의 감성과 2가지의 감성을 5가지의 임베딩 기법과 3종류의 분류 모델로 감성 분류 학습을 진행하였다. 감성 분류를 위해 Logistic Regression, Decision Tree, Random Forest 모델 등과 같은 보편적으로 많이 사용하는 머신러닝 분류 모델을 사용하였으며, 각각의 결과를 훈련 정확도와 테스트 정확도로 비교하였다. 실험 결과, 7가지 감성 분류 및 2가지 감성 분류 모두 사전훈련된 Word2vec가 대체적으로 우수한 정확도 성능을 보였다.