• The Journal of the Convergence on Culture Technology
• /
• v.9 no.1
• /
• pp.19-26
• /
• 2023

In this study, the public sensitivity of the 'MZ generation' was examined through the social media big data sensitivity analysis method. For the analysis, the consumer account SNS text was examined, and positive and negative emotional factors were presented by classifying external sensibilities and emotions of the MZ generation. In conclusion, the positive emotions of liking and interest in relation to the "MZ generation" were 72.1%, higher than the negative emotional ratio of 27.9%. In positive sensitivity, the older generation showed 'a favorable feeling for the individuality and dignifiedness of the MZ generation' and 'interest in the MZ generation with new values'. In contrast, the MZ generation has a favorable feeling for 'the fact that they are a generation of their own boldness, youthfulness and individuality' and 'small growthism'. Negative sensitivity outside the MZ generation was found to be 'A concern about the marriage avoidance, employment difficulties, debt investment, and resignation trends of the MZ generation', 'Hate the MZ generation who treats Kkondae' and 'Difficult to talk to the MZ generation'. On the other hand, the negative emotions felt by the MZ generation itself were 'Rejection of generalization', 'Rejection of generation and gender conflicts', 'Rejection of competition worse than the older generation', 'Relative failure of the rich era', and 'Sadness to live in a predicted climate disaster'. Therefore, the older generation should not look at the MZ generation in general, but as individuals, and should alleviate conflicts with intergenerational understanding and empathy. there is a need for community consideration to solve generational conflicts, gender conflicts, and environmental problems.

• Informatization Policy
• /
• v.30 no.1
• /
• pp.41-66
• /
• 2023

This study aims to reveal the direction of municipal ordinances for smart cities, while focusing on 74 municipal ordinances from 72 municipal governments through topic modeling. As a result, the main keywords that show a high frequency belong to establishment and operations of the Smart City Committee. From the result of topic modeling Latent Dirichlet Allocation(LDA), it classifies municipal ordinances for smart cities into eight topics as follows: Topic 1(security for process of smart cities), Topic 2(promotion of smart city industry), Topic 3(composition of a smart city consultative body for local residents), Topic 4(support system for smart cities), Topic 5(management for personal information), Topic 6(use of smart city data), Topic 7(implementation for intelligent public administration), and Topic 8(smart city promotion). As for topic categorization by region, Topics 5, 6, and 8 which are mostly related to the practical operation of smart cities have a significant portion of municipal ordinances for smart cities in the Seoul metropolitan area. Then, Topics 2, 3, and 4 which are mostly related to the initial implementation of smart cities have a significant portion of municipal ordinances for smart cities in provincial areas.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
• /
• v.7 no.4
• /
• pp.299-314
• /
• 2017

Technological advances in media have expanded users' consciousness. At the same time, users have changed from passive into active voice by interacting media. The emergence of mobile made different structures and contents compared to the past. Especially, Korean culture of mobile converted original media channels to contents in a category. Plus, the usage structure of internet of this time converges in massive portal sites. It is because that the structure has aspect of emitting through remediation in the sites. Also, Korean massive portal sites have provided specific service named 'real-time issues'. This is not only the unique way of offering information that exists in Korea but also high usability of getting issues. We therefore considered the meaning of durability of real-time issues in the view of journalism, compared original media channels. Then, this paper identified the user attributes for acquisition of information following ways using informal and formal data from Korean massive portal sites named 'Daum' and 'Naver'.

• Journal of the Korea Society of Computer and Information
• /
• v.28 no.7
• /
• pp.155-164
• /
• 2023

In this paper, we examine the influence of Environmental, Social, and Governance (ESG)-related content on the success of online crowdfunding proposals. Along with the increasing significance of ESG standards in business, investment proposals incorporating ESG concepts are now commonplace. Due to the ESG trend, conventional wisdom holds that the majority of proposals with ESG concepts will have a higher rate of success. We investigate by analyzing over 9000 online business presentations found in a Kickstarter dataset to determine which characteristics of these proposals led to increased investment. We first utilized lexicon-based measurement and Feature Engineering to determine the relationship between environment and society scores and financial indicators. Next, Logistic Regression is utilized to determine the effect of including environmental and social terms in a project's description on its ability to obtain funding. Contrary to popular belief, our research found that microentrepreneurs were less likely to succeed with proposals that focused on ESG issues. Our research will generate new opportunities for research in the disciplines of information science and crowdfunding by shedding new light on the environment of online micro-entrepreneurship.

• Industry Promotion Research
• /
• v.8 no.3
• /
• pp.181-199
• /
• 2023

E-commerce is gradually upgrading from traditional text and image formats to short video and livestreaming formats. Livestreaming e-commerce enriches the content and forms of information dissemination and product display, enhances the consumer's shopping experience, and gradually becomes the mainstream new consumer scene. However, there are many negative phenomena in the development of livestreaming e-commerce, such as false propaganda, counterfeit goods, and various negative events, which seriously affect the level of consumer trust in livestreaming e-commerce. Trust is the core competitive factor of livestreaming e-commerce. Based on previous research on trust theory and combined with the characteristic elements of "people, goods, and scenes" of livestreaming e-commerce, this article constructs a trust model for livestreaming e-commerce, proposes hypotheses, and proves through empirical research that factors such as store characteristics, livestream host characteristics, brand image, product information, platform reputation, livestreaming situation, and trust tendency have a significant positive impact on consumer trust. Based on the research conclusions, this article provides insights and management suggestions, such as emphasizing the construction of store characteristic indicators, creating desirable livestream host characteristics, focusing on product brand building and selection, maintaining the display of product information, selecting suitable livestreaming platforms, and creating rich content for livestreaming situations.

• Journal of Environmental Impact Assessment
• /
• v.32 no.6
• /
• pp.556-576
• /
• 2023

This study attempted to find a way to utilize idle spaces in rural areas as a way to respond to rural extinction. Based on the keywords "startup," "youth start-up," and "youth start-up+rural," start-up+rural," the study sought to identify the perception of idle facilities in rural areas through the keywords "Idle facilities" and "closed schools." The study presented basic data for policy direction and plan search by reviewing frequency analysis, major keyword analysis, network analysis, emotional analysis, and domestic and foreign cases. As a result of the analysis, first, it was found that idle facilities and school closures are acting importantly as factors for regional regeneration. Second, in the case of youth startups in rural areas, it was found that not only education on agriculture but also problems for residence should be solved together. Third, in the case of young people, it was confirmed that it was necessary to establish digital utilization for agriculture by actively starting a business using digital. Finally, in order to attract young people and revitalize the region through best practices at home and abroad, policy measures that can serve as various platforms such as culture and education as well as startups should be presented in connection with local residents. These results are significant in that they presented implications for youth start-ups in rural areas by reviewing start-up recognition for the influx of young people as one of the alternatives for the use of idle facilities and regional regeneration, and if additional solutions are presented through field surveys, they can be used to set policy goals that fit the reality.

• Phonetics and Speech Sciences
• /
• v.15 no.4
• /
• pp.109-118
• /
• 2023

Cardiac arrest is a critical medical emergency where immediate response is essential for patient survival. This is especially true for Out-of-Hospital Cardiac Arrest (OHCA), for which the actions of emergency medical services in the early stages significantly impact outcomes. However, in Korea, a challenge arises due to a shortage of dispatcher who handle a large volume of emergency calls. In such situations, the implementation of a machine learning-based OHCA detection program can assist responders and improve patient survival rates. In this study, we address this challenge by developing a machine learning-based OHCA detection program. This program analyzes transcripts of conversations between responders and callers to identify instances of cardiac arrest. The proposed model includes an automatic transcription module for these conversations, a text-based cardiac arrest detection model, and the necessary server and client components for program deployment. Importantly, The experimental results demonstrate the model's effectiveness, achieving a performance score of 79.49% based on the F1 metric and reducing the time needed for cardiac arrest detection by 15 seconds compared to dispatcher. Despite working with a limited dataset, this research highlights the potential of a cardiac arrest detection program as a valuable tool for responders, ultimately enhancing cardiac arrest survival rates.

• The Transactions of the Korea Information Processing Society
• /
• v.13 no.5
• /
• pp.209-216
• /
• 2024

Real estate market prices are determined by various factors, including macroeconomic variables, as well as the influence of a variety of unstructured text data such as news articles and social media. News articles are a crucial factor in predicting real estate transaction prices as they reflect the economic sentiment of the public. This study utilizes sentiment analysis on news articles to generate a News Sentiment Index score, which is then seamlessly integrated into a real estate price prediction model. To calculate the sentiment index, the content of the articles is first summarized. Then, using AI, the summaries are categorized into positive, negative, and neutral sentiments, and a total score is calculated. This score is then applied to the real estate price prediction model. The models used for real estate price prediction include the Multi-head attention LSTM model and the Vector Auto Regression model. The LSTM prediction model, without applying the News Sentiment Index (NSI), showed Root Mean Square Error (RMSE) values of 0.60, 0.872, and 1.117 for the 1-month, 2-month, and 3-month forecasts, respectively. With the NSI applied, the RMSE values were reduced to 0.40, 0.724, and 1.03 for the same forecast periods. Similarly, the VAR prediction model without the NSI showed RMSE values of 1.6484, 0.6254, and 0.9220 for the 1-month, 2-month, and 3-month forecasts, respectively, while applying the NSI led to RMSE values of 1.1315, 0.3413, and 1.6227 for these periods. These results demonstrate the effectiveness of the proposed model in predicting apartment transaction price index and its ability to forecast real estate market price fluctuations that reflect socio-economic trends.

• Journal of The Korean Association For Science Education
• /
• v.44 no.1
• /
• pp.39-55
• /
• 2024

This study aimed to examine research trends related to Natural Language Processing (NLP) in science education by analyzing 37 domestic and international documents that utilized NLP techniques in the field of science education from 2011 to September 2023. In particular, the study systematically analyzed the content, focusing on the main application areas of NLP techniques in science education, the role of teachers when utilizing NLP techniques, and a comparison of domestic and international perspectives. The analysis results are as follows: Firstly, it was confirmed that NLP techniques are significantly utilized in formative assessment, automatic scoring, literature review and classification, and pattern extraction in science education. Utilizing NLP in formative assessment allows for real-time analysis of students' learning processes and comprehension, reducing the burden on teachers' lessons and providing accurate, effective feedback to students. In automatic scoring, it contributes to the rapid and precise evaluation of students' responses. In literature review and classification using NLP, it helps to effectively analyze the topics and trends of research related to science education and student reports. It also helps to set future research directions. Utilizing NLP techniques in pattern extraction allows for effective analysis of commonalities or patterns in students' thoughts and responses. Secondly, the introduction of NLP techniques in science education has expanded the role of teachers from mere transmitters of knowledge to leaders who support and facilitate students' learning, requiring teachers to continuously develop their expertise. Thirdly, as domestic research on NLP is focused on literature review and classification, it is necessary to create an environment conducive to the easy collection of text data to diversify NLP research in Korea. Based on these analysis results, the study discussed ways to utilize NLP techniques in science education.

• Journal of Navigation and Port Research
• /
• v.48 no.1
• /
• pp.34-48
• /
• 2024

As global supply chain risks proliferate unpredictably, the high interdependence of port and logistics industry intensifies the risk burden. This study conducted fundamental research to explore diverse safety issues in domestic ports. Utilizing news article data about Busan Port, we employed LDA topic modeling and time-series linear regression to understand key safety trends. Over the past 30 years, Busan Port faced nine major safety issues-maritime safety, import cargo inspection, labor strikes, and natural disasters emerged cyclically. Major port safety issues in Busan Port are primarily characterized by an unpredictable nature, falling under socio-environmental and natural phenomena types, indicating a significant impact of global uncertainty. Therefore, systematic policies need to be formulated based on identified port safety issues to enhance port safety in Busan Port. Additionally, there is a need to strengthen the resilience of port safety for unpredictable risk situations. In conclusion, advanced research activities are necessary to promote port safety enhancement in response to dynamically changing social conditions.