• Fashion & Textile Research Journal
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• v.18 no.1
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• pp.48-62
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• 2016

Consumers have come to demand high quality, affordable prices, and innovative product designs of the outdoor wear market due to their well-being and leisure oriented lifestyle. A new system of business in outdoor wear has emerged in the process through which corporations have endeavored to satisfy such consumer needs. Outdoor wear brands have utilized social network services (SNS) such as Facebook and Twitter as means of marketing and have built close relations with consumers based on communication through these media. Recently, explosively escalating SNS data are referred to as social big data, and now that every consumer online is a commentator, reviewer, and publisher, the outdoor wear market and all of its brands have to stop talking and start listening to how they are perceived. Therefore, this study employs Social $Metrics^{TM}$, a social big data analysis solution by Daumsoft, Inc., to verify changes in the allusions related to outdoor wear market found on SNS. This study aims to identify changes in consumer perceptions of outdoor wear based on changes in outdoor wear search words and trends in positive and negative public opinion found in SNS social big data. In addition, products of interest, the major brands mentioned, the attributes taken into consideration during purchases of products, and consumers' psychology were categorized and analyzed by means of keywords related to outdoor wear brands found on SNS. The results of this study will provide fundamental resources for outdoor wear brands' market entry and brand strategy implementation in the future.

• Convergence Security Journal
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• v.21 no.2
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• pp.19-28
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• 2021

Korea is promoting a digital new deal policy for the digital transformation and innovation accelerating of the industry. However, because of the strict existing data-related laws, there are still restrictions on the industry's use of data for the digital new deal policy. In order to solve this issue, a revised bill of the Data 3 Act has been proposed, but there is still insufficient discussion on how it will actually affect the activation of data use in the industry. Therefore, this study aims to analyze the perception of public opinion on the Data 3 Act and the implications of the revision of the Data 3 Act. To this end, the revision of the Data 3 Act and related research trends were analyzed, and the perception of the Data 3 Act was analyzed using a big data analysis technique. According to the analysis results, while promoting the vitalization of the data industry in line with the purpose of the revision, the Data 3 Act has a concern that it focuses on specific industries. The results of this study are meaningful in providing implications for future improvement plans by analyzing online perceptions of the industrial impact of the Data 3 Act in the early stages of implementation through big data analysis.

• The Journal of the Korea Contents Association
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• v.21 no.4
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• pp.628-644
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• 2021

The main purpose of this study is to search for variables that influence the perception of news of YouTube current affairs and political channel users. Existing studies have focused on providing normative criticism by examining the public opinion influence of YouTube channels, which play a role similar to the media, in terms of political polarization, fake news, and confirmation bias. However, this study attempts to examine the changes and meanings of users' perception of news with the advent of YouTube. To this end, an online survey was conducted for users with experience in using YouTube's current affairs and political channels. As a result of the study, it was found that the news perception of YouTube current affairs and political channel users was mixed with the perception of news from the perspective of professional journalism and the perception of newly added news in the digital environment. Based on these results, the researcher examined the implications of the professional news media's response direction to the platform environment.

• Journal of Home Health Care Nursing
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• v.29 no.3
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• pp.278-287
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• 2022

Purpose: To analyze Korean nurse-related channels and video titles on YouTube, the world's largest online video sharing and social media platform, to clarify public opinion and image of nurses. We seek utilization strategies and measures through current status analysis. Methods: Data is collected by crawling video information related to Korean nurses, and correlation is analyzed with frequent word analysis and keyword network analysis. Results: Through the YouTube algorithm, 2,273 videos of 'Nurse' were analyzed in order of recent views, relevance, and rating, and 2,912 videos searched for with the keyword 'Nurse + Hospital, COVID-19, Awareness, University, National Examination' were analyzed. Numerous videos were uploaded, and nursing work that was uploaded in the form of a vlog recorded a high number of views. Conclusion: We could see if the YouTube video shows images of nurses. It has been confirmed that various information is being exchanged rather than information just for promotional purposes.

• Journal of People, Plants, and Environment
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• v.23 no.2
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• pp.233-243
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• 2020

This study collects social big data used in various fields in the past 9 years and explains the patterns of major keywords of the arboretums and botanical gardens to use as the basic data to establish operational strategies for future arboretums and botanical gardens. A total of 6,245,278 cases of data were collected: 4,250,583 from blogs (68.1%), 1,843,677 from online cafes (29.5%), and 151,018 from knowledge search engine (2.4%). As a result of refining valid data, 1,223,162 cases were selected for analysis. We came up with keywords through big data, and used big data program Textom to derive keywords of arboretums and botanical gardens using text mining analysis. As a result, we identified keywords such as 'travel', 'picnic', 'children', 'festival', 'experience', 'Garden of Morning Calm', 'program', 'recreation forest', 'healing', and 'museum'. As a result of keyword analysis, we found that keywords such as 'healing', 'tree', 'experience', 'garden', and 'Garden of Morning Calm' received high public interest. We conducted word cloud analysis by extracting keywords with high frequency in total 6,245,278 titles on social media. The results showed that arboretums and botanical gardens were perceived as spaces for relaxation and leisure such as 'travel', 'picnic' and 'recreation', and that people had high interest in educational aspects with keywords such as 'experience' and 'field trip'. The demand for rest and leisure space, education, and things to see and enjoy in arboretums and botanical gardens increased than in the past. Therefore, there must be differentiation and specialization strategies such as plant collection strategies, exhibition planning and programs in establishing future operation strategies.

• Korean Journal of Clinical Pharmacy
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• v.32 no.2
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• pp.93-105
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• 2022

Objectives: This study aimed to identify the opinions of Gyeongsangbuk-do residents on out-of-hours (OOH) pharmacies and to examine the operating experiences of pharmacists who are operating OOH pharmacies in other areas. Methods: Cross-sectional survey was carried out for 1,000 Gyeongbuk residents employing a questionnaire via online or face-to-face, and 82 pharmacists who currently operate OOH pharmacies employing a postal questionnaire. Out of eighty-two, 46 pharmacists replied (response rate 56.1%). Results: As for the necessity of introducing OOH pharmacies in Gyeongsangbuk-do, 84.9% answered more than necessary. 86.1% favored the local government support for OOH pharmacies. The necessity of OOH pharmacies was highly evaluated among participants who experienced to be unable to use medicines or services in out of service hours, regardless of their characteristics or health condition. County residents consistently put a positive opinion for the necessity of OOH pharmacies if they have elderly family member(s), while city residents had significant differences across subgroups depending on their conditions (family members, household economics, health status, etc.). Almost all (95.7%) pharmacist participants highly evaluated the necessity of OOH pharmacies and the majority of them (63.0%) felt satisfied. However, 60.9% of participants have ever considered closing their OOH pharmacy business due to private, business management and professional reasons. Conclusion: This study made suggestions to address anticipated issues for the Gyeongbuk-style OOH pharmacy model.

• International Journal of Computer Science & Network Security
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• v.22 no.5
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• pp.320-326
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• 2022

The use of the Internet has become commonplace for billions of people on the planet. The rapid development of technology, in particular, mobile gadgets, has provided access to communication anywhere, anytime. At the same time, there are growing concerns about the behavior of people on the Internet, in particular, towards each other and social groups in general. This raises the issue of human rights in today's information society. In this study, we focused on human rights such as the right to privacy, confidentiality, freedom of expression, the right to be forgotten, etc. We point to some differences in this regard, in particular between the EU, etc. In addition, we describe the latest legal regulation in this aspect in European countries. Such methods as systemic, factual, formal and legal, to show the factors of formation and development of human rights in the context of digitalization were used. The authors indicate which of them deserve the most attention due to their prevalence and relevance. Thus, we concluded that the technological development of social communications has laid the groundwork for a legal settlement of privacy and opinion issues on the Internet. Simultaneously, jurisdictions address issues on every aspect of human rights on the Internet, based on previous norms, case law, and principles of law. It is concluded that human rights legislation on the Internet will continue to be actively developed to ensure a balance of private and public interests, safe online access and unimpeded access to it.

• Journal of Distribution Science
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• v.21 no.1
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• pp.85-93
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• 2023

Purpose: This research is intended to analyze how distribution of brand communication of a Soft Drink brand on brand image mediated through electronic word of mouth on packaged carbonated drink in Indonesian Gen-Z. This research also aims to find out how electronic word of mouth can have a role in creating a brand image for Indonesia Gen-Z. Research design, data and methodology: This research is using a quantitative approach with purposive sampling technique, a survey was conduct online and the number of samples being 384 responders who are spread all over Indonesia. The questionnaire construct was designed based on several variables, such as brand communication, brand image, and e-WOM. E-WOM was positioned as a mediating variable in this research. Brand Communication indicators consist of event and experience, public relation and publicity, direct marketing and personal selling. Meanwhile brand image consists of Attributes, Benefits, and Attitudes. E-WOM indicators consist of intensity, balance of opinion, and content. Results: The result of this research being (1) There is a significant influence between brand communication and brand image. (2) There is a significant influence between brand communication and electronic word-of-mouth. And (3) There is a significant influence between brand communication and brand image mediated through electronic word-of-mouth. Conclusion: The findings of this research prove that there is significant influence between brand communication, brand image and electronic word-of-mouth, this study also provide several information about how other factor affect the distribution of brand communication.

• International Journal of Computer Science & Network Security
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• v.24 no.2
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• pp.79-88
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• 2024

The use of the social media has become part of our daily life activities. The social web channels provide the content generation facility to its users who can share their views, opinions and experiences towards certain topics. The researchers are using the social media content for various research areas. Sentiment analysis, one of the most active research areas in last decade, is the process to extract reviews, opinions and sentiments of people. Sentiment analysis is applied in diverse sub-areas such as subjectivity analysis, polarity detection, and emotion detection. Stance classification has emerged as a new and interesting research area as it aims to determine whether the content writer is in favor, against or neutral towards the target topic or issue. Stance classification is significant as it has many research applications like rumor stance classifications, stance classification towards public forums, claim stance classification, neural attention stance classification, online debate stance classification, dialogic properties stance classification etc. This research study explores different feature sets such as lexical, sentiment-specific, dialog-based which have been extracted using the standard datasets in the relevant area. Supervised learning approaches of generative algorithms such as Naïve Bayes and discriminative machine learning algorithms such as Support Vector Machine, Naïve Bayes, Decision Tree and k-Nearest Neighbor have been applied and then ensemble-based algorithms like Random Forest and AdaBoost have been applied. The empirical based results have been evaluated using the standard performance measures of Accuracy, Precision, Recall, and F-measures.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.47 no.1
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• pp.41-50
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• 2024

Korea is facing a significant problem with historically low fertility rates, which is becoming a major social issue affecting the economy, labor force, and national security. This study analyzes the factors contributing to the regional gap in fertility rates and derives policy implications. The government and local authorities are implementing a range of policies to address the issue of low fertility. To establish an effective strategy, it is essential to identify the primary factors that contribute to regional disparities. This study identifies these factors and explores policy implications through machine learning and explainable artificial intelligence. The study also examines the influence of media and public opinion on childbirth in Korea by incorporating news and online community sentiment, as well as sentiment fear indices, as independent variables. To establish the relationship between regional fertility rates and factors, the study employs four machine learning models: multiple linear regression, XGBoost, Random Forest, and Support Vector Regression. Support Vector Regression, XGBoost, and Random Forest significantly outperform linear regression, highlighting the importance of machine learning models in explaining non-linear relationships with numerous variables. A factor analysis using SHAP is then conducted. The unemployment rate, Regional Gross Domestic Product per Capita, Women's Participation in Economic Activities, Number of Crimes Committed, Average Age of First Marriage, and Private Education Expenses significantly impact regional fertility rates. However, the degree of impact of the factors affecting fertility may vary by region, suggesting the need for policies tailored to the characteristics of each region, not just an overall ranking of factors.