• The Journal of the Korea Contents Association
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• v.20 no.4
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• pp.151-158
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• 2020

SNS on the mobile platform is an essential element and tool for communication and has become a part of life for many people. Having been accustomed to non-face-to-face communication, people today have chosen to use emoticons instead of text to express their feelings and the use of emoticons is constantly growing. This is because the emoticons in various styles of drawings and movements can evoke emotional and sentimental reactions in users and express their tastes in addition to feelings. The current study was conducted to analyze the use of initial emoticon characters released by two most leading SNS platforms in Korea--Kakao for Kakao Talk and Naver for Line--and their expansion to various platform businesses. Based on the cases of the two companies, it discussed the development and goals of Korea-made emoticons in the future as cultural contents.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.6
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• pp.45-52
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• 2016

The purpose of this study was to investigate the meaning of conflict experience in cooperative learning activities of pre-service early childhood teachers. The subjects were 85 pre-service early childhood teachers in W university. The data were collected through unstructured interviews and journal writings of the participants. The study results were as follow. First, pre-service early childhood teacher's conflict experiences in cooperative activity are team meeting, fair participation and evaluation, and conflict of the personal relations. Second, pre-service early childhood teacher's conflict resolution experiences in cooperative activity are autonomy of the team meeting time, reflective thinking, sentimental support, recognition of others, and solving problems by the time spending together. Third, the meanings of conflict experience in cooperative activity are formation of felt responsibility, self-growth through consideration of others, reciprocity, and recognition of the meaning of cooperation.

• The Journal of the Korea Contents Association
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• v.22 no.7
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• pp.89-101
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• 2022

COVID-19 is significantly changing consumers' demand and habits. In order to understand consumer characteristics and find effective advertising directions in the post-COVID-19 era, this study set young consumers who are more sensitive to market changes and technological transformation from a subjective perspective of advertising audiences. Through the Q methodology, the advertising development model in the post-COVID-19 era was derived exploratively by examining their cognitive status of advertisements in the post-COVID-19 era. The model consists of three types of advertisements: "demand mining online ads" that value consumer demand and adapt to online shopping paths, "added value creation experiential ads" that value derived value and consumer experiences, and "practical and sentimental value creative ads" based on pragmatism and emotional values. In addition, this study also suggested for the sustainable practice of advertising in the post-COVID-19 era in various aspects, such as "seeking multidimensional values," "expanding consumer experience," and "mining and leading demand.

• The Journal of Sustainable Design and Educational Environment Research
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• v.19 no.1
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• pp.3-12
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• 2020

Many libraries have recently become enlarged and industrialized. Spaces dedicated to natural environments and climates in libraries have been isolated, and spaces that take natural environments into consideration have only recently started to receive attention. People all around the world enjoy reading books in nature. Reading is interpreted as the same context as the desire to go somewhere higher. Contemporary people have discovered ways to enjoy reading books along with nature by establishing bookshelves in mountains, forests, or green fields. These people have created libraries that place nature as the protagonist. In spatial terms, natural environments mainly encompass scientific and systemic concepts and embrace a sentimental approach to the natural environments of local areas not previously considered. The purpose of this research study is to present the direction for spatial planning that harmonizes nature with space, and to propose the spatial planning of a "small library" by applying natural environmental characteristics.

• Journal of the Korea Society of Computer and Information
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• v.25 no.11
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• pp.41-50
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• 2020

Sentimental analysis begins with the search for words that determine the sentimentality inherent in data. Managers can understand market sentimentality by analyzing a number of relevant sentiment words which consumers usually tend to use. In this study, we propose exploring performance of feature selection methods embedded with Particle Swarm Optimization Multi Objectives Evolutionary Algorithms. The performance of the feature selection methods was benchmarked with machine learning classifiers such as Decision Tree, Naive Bayesian Network, Support Vector Machine, Random Forest, Bagging, Random Subspace, and Rotation Forest. Our empirical results of opinion mining revealed that the number of features was significantly reduced and the performance was not hurt. In specific, the Support Vector Machine showed the highest accuracy. Random subspace produced the best AUC results.

• Journal of Convergence for Information Technology
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• v.9 no.11
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• pp.81-91
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• 2019

Recently, social network service (SNS) is actively used by public. Among them, Twitter has a lot of tweets including sentiment and it is convenient to collect data through open Aplication Programming Interface (API). In this paper, we analyze social issues and suggest the possibility of using them in marketing through sentimental information of users. In this paper, we collect twitter text about social issues and classify as positive or negative by sentiment classifier to provide qualitative analysis. We provide a quantitative analysis by analyzing the correlation between the number of like and retweet of each tweet. As a result of the qualitative analysis, we suggest solutions to attract the interest of the public or consumers. As a result of the quantitative analysis, we conclude that the positive tweet should be brief to attract the users' attention on the Twitter. As future work, we will continue to analyze various social issues.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.40 no.4
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• pp.171-182
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• 2017

Most people seek a happy life and happiness positively affects sentiment, satisfaction with life, creativity, human relationship, business productivity, and even health and life extension. However, according to a survey in 2013, subjective happiness of adolescents (including university students) was very low compared to other age groups in Korea. Therefore this paper examined the effects of job-seeking stress, appearance recognition, financial situation, trust in government, and locus of control on university students' happiness using SEM (structural equation modeling). 207 university students in Seoul, Korea have been surveyed. At first, an initial experimental SEM model among these variables has been set up and reliability analysis has been conducted. Then multiple regression analyses on job-seeking stress and happiness as well as SEM analysis have been conducted. As a result of these analyses, the SEM model has been revised two times. The final SEM model passed the goodness-of-fit test (using RMR, GFI, NFI, CFI, and IFI indices). The final SEM model showed the followings. First, Higher job-seeking stress (especially sentimental part, rather than environment or action related parts) negatively affects happiness. Second, Trust in government also affects happiness both directly and indirectly. Third, Locus of control is affected both by trust in government and financial situation. Fourth, appearance recognition heavily affects job-seeking stress. In addition, appearance importance is higher than appearance interest, meaning that students who are not very interested in appearance usually recognize the importance of appearance. Finally, happiness is affected neither financial situation nor appearance recognition. Therefore, even either they are in a poor financial situation or not happy with their appearance, they can be happy if they have firm locus of control.

• The Journal of the Convergence on Culture Technology
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• v.6 no.2
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• pp.449-454
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• 2020

This paper proposes a machine learning-based emotion analysis system that detects a user's depression through their SNS posts. We first made a list of keywords related to depression in Korean, then used these to create a training data by crawling Twitter data - 1,297 positive and 1,032 negative tweets in total. Lastly, to identify the best machine learning model for text-based depression detection purposes, we compared RNN, LSTM, and GRU in terms of performance. Our experiment results verified that the GRU model had the accuracy of 92.2%, which is 2~4% higher than other models. We expect that the finding of this paper can be used to prevent depression by analyzing the users' SNS posts.

• Journal of Digital Convergence
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• v.19 no.11
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• pp.471-483
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• 2021

The purpose of this study is to find out audience' response of virtual influencer at the starting line of virtual influencer marketing. Therefore, posts, comments, number of likes, and video reviews were collected from Instagram of virtual influencers active in Korea. Python 3.7 and Textom were used for data collection and analysis. Sentimental analysis showed that the rate of positivity was higher than the rate of negativity and neutrality. The appearance of virtual influencer was found to be a major factor in both positive and negative. Consumers' interest in virtual influencer could be inferred from the neutral sensibility. This study is meaningful in that it presented data to help establish strategies for virtual influencer marketing by examining consumer reactions to virtual influencer and identifying factors of positive and negative emotions toward virtual influencer.

• KIPS Transactions on Software and Data Engineering
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• v.10 no.4
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• pp.153-160
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• 2021

With the advent of the "age of video" due to the simplification of video content production and the convenience of broadcasting channel operation, review videos on various products are drawing attention. We proposes RASIA, an integrated reliability analysis system based on verbal and nonverbal sentiment analysis of review videos. RASIA extracts and quantifies each emotional value obtained through language sentiment analysis and facial analysis of the reviewer in the video. Subsequently, we conduct an integrated reliability analysis of standardized verbal and nonverbal sentimental values. RASIA provide an new objective indicator to evaluate the reliability of the review video.