• Journal of Korea Game Society
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• v.15 no.4
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• pp.145-156
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• 2015

Existing researches have been limited to one-dimensional analysis of game experience (enjoyment, addictive user, usability). However, we considered to analyze complex sentiments of mobile game users due to diffusion of multitasking in these days. In this study, We focused on 'collective sentiments' of mobile game users and studied 'connected emotions and mental model' of them. To support theoretical assumption, we analyzed social data which reflect intention and unintended behavior of users. As a result, multiple consumption of service, diversified patterns of information recommendation and quest experience based on networking were critical to mobile game UX.

• Journal of the Korea Convergence Society
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• v.9 no.1
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• pp.419-431
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• 2018

In this paper, we propose a novel method for monitoring mood trend of Twitter users by analyzing their daily tweets for a long period. Then, to more accurately understand their tweets, we analyze all types of content in tweets, i.e., texts and emoticons, and images, thus develop a multimodal sentiment analysis method. In the proposed method, two single-modal analyses first are performed to extract the users' moods hidden in texts and images: a lexicon-based and learning-based text classifier and a learning-based image classifier. Thereafter, the extracted moods from the respective analyses are combined into a tweet mood and aggregated a daily mood. As a result, the proposed method generates a user daily mood flow graph, which allows us for monitoring the mood trend of users more intuitively. For evaluation, we perform two sets of experiment. First, we collect the data sets of 40,447 data. We evaluate our method via comparing the state-of-the-art techniques. In our experiments, we demonstrate that the proposed multimodal analysis method outperforms other baselines and our own methods using text-based tweets or images only. Furthermore, to evaluate the potential of the proposed method in monitoring users' mood trend, we tested the proposed method with 40 depressive users and 40 normal users. It proves that the proposed method can be effectively used in finding depressed users.

• Science of Emotion and Sensibility
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• v.20 no.4
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• pp.15-30
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• 2017

The purpose of this study was to verify the basic emotion theory based on the emotion-related research using functional brain imaging technology. For this purpose, a meta-analysis on the functional magnetic resonance imaging (fMRI) studies was performed. Six individual emotions-joy, happiness, fear, anger, disgust, sadness-were selected. In order to collect the fMRI data of individual emotions, we searched the electronic journals such as Medline, PsychInfo, PubMed for the past 10 years. fMRI experiment data aimed at healthy subjects for 6 emotions were collected, and only studies reported in Talairach or MNI standard coordinate system were included. In order to eliminate the difference between Talairach and MNI coordinate systems, we analyzed fMRI data based on the Talairach coordinate system. A meta-analysis using GingerALE 2.3 program adopting the activation likelihood estimates (ALE) techniques was performed. In this study, we confirmed that the individual emotions are associated with consistent and distinguishable regional brain responses within the framework of the basic emotion theory. The conclusion of this study of the brain areas associated with each individual emotional reaction was substantially consistent with the results of existing review articles. Finally, the limitations of this study and some suggestions for the future research were presented.

• Journal of Korea Society of Industrial Information Systems
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• v.25 no.5
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• pp.91-102
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• 2020

The Internet of Things (IoT) is characterized as the market where various companies compete for the same consumers. Thus, there are differences in functions and performance provided by the main business area and other characteristics of the service providers. This paper investigates whether satisfaction with the service provided depends on the characteristics of the operator by using sentiment analysis of comments. To achieve this goal, word importance analysis and sensitivity analysis are conducted on 34,310 reviews of 41 applications registered in the Google Play. The review analysis was conducted at various levels, including TD-IDF (Term frequency-inverse document frequency) value of keywords, service sectors, the origin of providers, and domestic/foreign providers. The results show that users' overall assessment of IoT services was found to be low, and smart homes received relatively high reviews compared to other services, and manufacturing-based and overseas providers received relatively higher evaluations than others.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.6 no.10
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• pp.549-564
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• 2016

Due to high cost of domestic production structure, steep growth of China's manufacturing business, and increase in oversea's production, building integrated system to support user-centered product design system based on cognitive and affective information is required to restore development of domestic manufacturing business. This paper put purpose on analysing requirements of end users, especially on information equipment business which works as a major industry in manufacturing businesses, and planning system design direction, prior to constructing user-centered product design support system based on cognitive and affective information. Research was conducted to identify current manufacturing process, application data on manufacturing, availability of cognitive and affective information data and its method of use, and necessity of user-centered product design support system based on cognitive and affective information, by carrying out in-depth interview with 6 related manufacturing companies. Need for user's character information was deducted from the interview, especially cognitive and affective information which is demanding for small to medium manufacturing business to research on its own.

• Journal of the Korea Convergence Society
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• v.8 no.7
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• pp.323-330
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• 2017

Emotion in early childhood has been observed to make an important effect on behavioral development. The teacher has coached to develop good behavior based on considering emotional response rather than rational response. This study was to determine significance of emotional coaching for behavior development according emotion recognized by non-verbal measurement system developed specially in this study. The participants were 44 people and were asked to study in four experimental situation. The experiment was designed to four situation such as class without coaching, behavioral coaching, emotion coaching, and emotion coaching based on emotional recognition system. The dependent variables were subjective evaluation, behavioral amplitude, and HRC (Heart Rhythm Coherence) of heart response. The results showed the highest positive evaluation, behavioral amplitude, and HRC at emotion coaching based on emotional recognition system. In post-doc analysis, the subjective evaluation showed no difference between emotion coaching and system based emotion coaching. However, the behavioral amplitude and HRC showed a significant response between two coaching situation. In conclusion, quantitative data such as behavioral amplitude and HRC was expected to solve the ambiguity of subjective evaluation. The emotion coaching of teacher using emotional recognition system was can be to improve positive emotion and psychological stability for children.

• Science of Emotion and Sensibility
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• v.24 no.1
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• pp.91-104
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• 2021

This study explored users' emotional states identified from the wake-up words -"Hi, KIA!"- using a machine learning algorithm considering the user interface of passenger cars' voice. We targeted four emotional states, namely, excited, angry, desperate, and neutral, and created a total of 12 emotional scenarios in the context of car driving. Nine college students participated and recorded sentences as guided in the visualized scenario. The wake-up words were extracted from whole sentences, resulting in two data sets. We used the soundgen package and svmRadial method of caret package in open source-based R code to collect acoustic features of the recorded voices and performed machine learning-based analysis to determine the predictability of the modeled algorithm. We compared the accuracy of wake-up words (60.19%: 22%~81%) with that of whole sentences (41.51%) for all nine participants in relation to the four emotional categories. Accuracy and sensitivity performance of individual differences were noticeable, while the selected features were relatively constant. This study provides empirical evidence regarding the potential application of the wake-up words in the practice of emotion-driven user experience in communication between users and the artificial intelligence system.

• Science of Emotion and Sensibility
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• v.25 no.4
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• pp.129-138
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• 2022

In the context of the increasing applications of voice assistants in vehicles, we focused on the association between the visual appeal of the cars and the acoustic characteristics of the voice assistants. This study aimed to investigate the relationship between the visual appeal of the vehicle and the voice assistant based on their emotional characteristics. A total of 15 adjectives were used to assess the emotional characteristics of 12 types of cars and six types of voices. An online interview was carried out, instructing participants to match three adjectives with the presented car images or voices. This was followed with a brief interview to allow the participants to reflect on the adjective matches. Based on the assessments, we performed principal component analysis (PCA) to determine factors. We aimed to deploy the cars and voices and analyze the patterns of clustering. The PCA analysis revealed two factors profiled as "Light-Heavy" and "Comfortable-Radical." Both car and voice stimuli were deployed in a two-dimensional space showing the internal relationship within and between the two substances. Based on the coordination data, a hierarchical cluster grouped the 18 stimuli into four groups labeled as challenge, elegance, majesty, and vigor. This study identified two latent factors describing the emotional characteristics of both car images and voice types clustered into four groups based on their emotional characteristics. The coherent matches between car style and voice type are expected to address the design concept more successfully.

• Science of Emotion and Sensibility
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• v.20 no.4
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• pp.55-64
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• 2017

This study was performed to help the denim fabric planning which reflects the sensibility preference of university students. Objective characteristics, like color properties and mechanical properties, in 8 denim fabrics (5 cotton 100% fabrics and 3 cotton/polyurethane blended fabrics) were evaluated. And the color preference, subjective sensation and tactile preference of denim fabrics were investigated among the university students. The effect of color preference and tactile preference of denim fabrics on the purchase preference of denim slacks was also examined. Color preference of denim fabrics showed a significant difference according to the kind of denim fabrics. University students preferred purple blue denim fabrics that was measured low $-b^*$ value and low $C^*$ value among the color properties of denim fabrics. Among the mechanical properties of denim fabrics, surface property like MMD, MIU and SMD as well as shear property like 2HG5 were important elements affecting subjective sensation. While, tactile preferences showed a significant difference according to the fabrics. The tactile preferences of cotton/polyurethane blended denim fabrics was highly preferred, and that of heavy 100% cotton denim fabric was lowly preferred. And the subjective sensation affecting tactile preferences were in order of smoothness, softness, lightness. It is concluded that the color preference and tactile preference influenced upon the purchase preference of denim slacks, and color preference had a bigger effect upon the purchase preference.

• Science of Emotion and Sensibility
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• v.11 no.3
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• pp.301-312
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• 2008

Satisfaction of consumer preferences is a key factor for the success of the products. Therefore, design mangers try to develop the profitable products through the intensive survey on the consumer preferences. Although the studies on the preferable product design and the design factors have long been carried out, most of these studies dealt only with the design factors preferable for individual product category ignoring the relationship of the product categories which are related to each other. For designers and design managers, in this study, we propose the guidelines of successful product development by finding preferred common and distinct design factors through analysis of the relations between the consumer preferences and design factors in various portable electric devices. To this end, we analyzed the preferred common and distinct design factors from portable electric devices including the electronic dictionaries, notebook computers, cellular phones, and MP3 players. We used hierarchical regression analysis for the effects of the design factors on the preferences among the product categories and regression analysis for the effects among each product category. The analysis on the preferred common design factors among the four product categories revealed that consumers did not care about the whole body type but preferred white color, metallic and glassy texture in the body. Also, the preferred design factors in the each product category are as follows; oval body shape and black color in electronic dictionaries, white color, metallic and glassy texture in notebook computers, plastic texture in cellular phones, rectangular body shape and plastic texture in MP3 players. In the case of notebook computers, the preferred common and distinct design factors were the same. We expect these results will be helpful for designers and design managers to identify the preferred design factors to consider when developing the various portable electric devices.