• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.7
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• pp.504-509
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• 2020

This study analyzed the factors that affect the emotional intelligence of clinical dental hygienists' psychological well-being. The study was conducted from September 1, 2019 to November 30, 2019 with 180 dental hygienists living in Jeollabuk-do province. The data was analyzed by independent t-tests, one-way ANOVA, Scheffé test, Pearson's correlation coefficient, and stepwise multiple regression using SPSS 18.0. Psychological well-being has a significant correlation with emotional intelligence (r=.596, p<.001). Emotional intelligence of clinical dental hygienists was found to be significant in a suitable regression model (F=116.575, p<.05), and the explanatory power was 53.6%. The higher the psychological well-being was, the higher the emotional intelligence was. The factors related to emotional intelligence of clinical dental hygienists were psychological well-being, self-acceptance, positive relations to others, personal growth, environmental mastery and clinical experience. The results of this study show that psychological well-being is related to emotional intelligence. It is necessary to establish an effective strategy to enhance the psychological well-being of clinical dental hygienists and strengthen their emotional intelligence.

• The Journal of Society for e-Business Studies
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• v.27 no.1
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• pp.15-28
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• 2022

Due to recent expansion of online market such as clothing, utilizing customer review has become a major marketing measure. User review has been used as a tool of analyzing sentiment of customers. Sentiment analysis can be largely classified with machine learning-based and lexicon-based method. Machine learning-based method is a learning classification model referring review and labels. As research of sentiment analysis has been developed, multi-modal models learned by images and video data in reviews has been studied. Characteristics of words in reviews are differentiated depending on products' and customers' categories. In this paper, sentiment is analyzed via considering review data and metadata of products and users. Gated Recurrent Unit (GRU), Long Short-Term Memory (LSTM), Self Attention-based Multi-head Attention models and Bidirectional Encoder Representation from Transformer (BERT) are used in this study. Same Multi-Layer Perceptron (MLP) model is used upon every products information. This paper suggests a multi-modal sentiment analysis model that simultaneously considers user reviews and product meta-information.

• Journal of the Korea Institute of Building Construction
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• v.10 no.4
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• pp.59-65
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• 2010

Many Construction companies are making great efforts to prevent accidents on their work sites. Safety is one of the greatest success factors on a construction project. Nowadays, many safety tools are being applied to construction sites. In addition, an emotional safety culture is an important factor for promoting a "safety first" mindset on construction sites. Therefore, this research aims to examine the effectiveness of the emotional safety system using PIR (Pyroelectric Infrared Ray) sensors to improve the safety mindset in the building construction site. The results of this research revealed that many construction site workers are satisfied with the emotional safety system using sensors. In addition, it was found that voice safety systems give a positive impulse to the workers. By applying this system to construction sites, construction companies can improve safety and work productivity.

• The Journal of the Korea Contents Association
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• v.22 no.1
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• pp.74-85
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• 2022

Along with the change in the values of marriage and the prevalence of non-marriage in Korean society, a new form of family composition called unmarried birth or non-maritalism childbirth has appeared, and social discussion in taking place in connection with the problem of a decrease in the birthrate. Using sentiment analysis and social network analysis, this research explored how the people's sentiment and perception has changed toward 'nonmarital birth.' The data used is comments on news articles from the period of November 2020 to August 2021. As a result of the study, there were a lot of positive comments during the social issue period by marriage, whereas there were many negative comments from the policy agenda to the policy making period. As a result of co-occurrence network analysis, the topic of family norm, policy, and personal aspect appeared. This study is significant in that it revealed that negative perceptions prevailed during the policy-making process after the issue of unmarried births after the issue of unmarried births, and it became a cornerstone of social discussion on unmarried births

• Journal of the Korea Convergence Society
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• v.12 no.4
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• pp.31-42
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• 2021

The purpose of this study was to explore research topics and examine the trend in COVID19 related research papers. We identified eight topics using latent Dirichlet allocation and found acceptable validity in comparison with the structural topic model. The subtopics have been extracted using k-means clustering and plotted in PCA space. Additionally, we discovered the topics bearing negative tones and warning signs by sentiment analysis. The results flagged up the issues of the topics, Biomedical Related, International Dynamics and Psychological Impact. The findings could serve as a guideline for researchers who explore new research directions and policymakers who need to make decisions about which research projects to support.

• Journal of the Korean Regional Science Association
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• v.39 no.3
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• pp.35-48
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• 2023

This study analyzed the inflow factors of Yangjae Citizen's Forest Park using social big data generated online. To this end, the applicability of the emotional information analysis method is to be confirmed as a method of analyzing the perception of the city park and confirming the difference in the characteristics and use of the park. The analysis is based on big data, and as the core of the study is keyword network analysis, the methodology of the 'emotional information analysis method' patented by the author was applied. As a result of the analysis, among the influx factors of Yangjae Citizens' Forest recognized by citizens, the most positive emotional factor was derived as a factor related to 'park contents', and the negative emotional factor was derived as a factor related to 'park management'. These research results suggest that more in-depth program development and operation are needed to discover 'park contents' when implementing urban park revitalization support projects in the future

• Journal of the Korea Society of Computer and Information
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• v.29 no.6
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• pp.201-209
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• 2024

The COVID-19 pandemic has significantly impacted the aviation industry, leading to worldwide changes in travel restrictions and security measures. This study analyzes 59,818 reviews of 147 airlines from the SKYTRAX website between 2016 and 2023 to understand the changes in airline service satisfaction before and after the pandemic. Using sentiment analysis, the study compares overall satisfaction, review sentiment, and attributes influencing satisfaction. The results show a statistically significant (p<0.001) decrease in overall satisfaction post-COVID-19, with reduced positive sentiment and increased negative sentiment for all airline selection attributes, except cabin and in-flight services. Flight operation services had the most significant impact on overall satisfaction during both periods. This quantitative analysis of global major airlines' satisfaction attributes before and after COVID-19 contributes to enhancing future service satisfaction in the airline industry.

• Information Systems Review
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• v.22 no.3
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• pp.81-97
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• 2020

Recent trends in sentiment analysis have been focused on applying single label classification approaches. However, when considering the fact that a review comment by one person is usually composed of several topics or aspects, it would be better to classify sentiments for those aspects respectively. This paper has two purposes. First, based on the fact that there are various aspects in one sentence, aspect mining is performed to classify the emotions by each aspect. Second, we apply the multiple label classification method to analyze two or more dependent variables (output values) at once. To prove our proposed approach's validity, online review comments about musical performances were garnered from domestic online platform, and the multi-label classification approach was applied to the dataset. Results were promising, and potentials of our proposed approach were discussed.

• Journal of Digital Convergence
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• v.10 no.10
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• pp.139-146
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• 2012

The emotional factor has not been focused in e-learning studies. But the emotions of student are very important in e-learning because it is a self-regulated learning. This study is focused on the emotional factor in e-learning. This study examines the effect of perceived customer orientation to emotional presence, commitment and customer satisfaction in e-learning. The results of this study showed that the perceived customer orientation effect to the commitment about the learning and the customer satisfaction in e-learning.

• Proceedings of the Korea Information Processing Society Conference
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• 2016.10a
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• pp.636-639
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• 2016

빅데이터의 일종인 뉴스기사 중에 아이돌 그룹관련 뉴스기사는 아이돌 그룹의 대중적 인기에 힘입어 전체 연예계 기사 중에 점점 큰 비중을 차지하고 있다. 아이돌 그룹의 소속사는 여러 홍보 방법 중 뉴스기사의 노출을 통해 비교적 저렴한 비용으로 홍보하여 음원차트 순위 향상을 위해 노력하고 있다. 본 논문에서는 뉴스기사와 음원차트 간의 상관관계를 분석하여 뉴스기사의 노출이 효율적 홍보 수단 인지를 알아보기 위해 먼저 감성분석을 통해 긍정기사와 부정기사가 음원차트 순위에 미치는 영향을 분석하고, 뉴스기사의 수가 많을수록 음원차트 순위가 상승하는지에 대해 알아보고자 한다. 이를 위해 본 논문에서는 R 언어를 이용하여 데이터 수집을 위한 웹 크롤러 설계, 회귀분석을 이용한 감성사전 구축 및 감성분석, 마지막으로 피어스만 상관계수를 이용한 상관관계 분석을 수행한다.