• Journal of the Korean Society for information Management
• /
• v.30 no.1
• /
• pp.7-32
• /
• 2013

The goal of the present study is to identify the topic trend in the field of library and information science in Korea. To this end, we collected titles and s of the papers published in four major journals such as Journal of the Korean Society for information Management, Journal of the Korean Society for Library and Information Science, Journal of Korean Library and Information Science Society, and Journal of the Korean BIBLIA Society for library and Information Science during 1970 and 2012. After that, we applied the well-received topic modeling technique, Latent Dirichlet Allocation(LDA), to the collected data sets. The research findings of the study are as follows: 1) Comparison of the extracted topics by LDA with the subject headings of library and information science shows that there are several distinct sub-research domains strongly tied with the field. Those include library and society in the domain of "introduction to library and information science," professionalism, library and information policy in the domain of "library system," library evaluation in the domain of "library management," collection development and management, information service in the domain of "library service," services by library type, user training/information literacy, service evaluation, classification/cataloging/meta-data in the domain of "document organization," bibliometrics/digital libraries/user study/internet/expert system/information retrieval/information system in the domain of "information science," antique documents in the domain of "bibliography," books/publications in the domain of "publication," and archival study. The results indicate that among these sub-domains, information science and library services are two most focused domains. Second, we observe that there is the growing trend in the research topics such as service and evaluation by library type, internet, and meta-data, but the research topics such as book, classification, and cataloging reveal the declining trend. Third, analysis by journal show that in Journal of the Korean Society for information Management, information science related topics appear more frequently than library science related topics whereas library science related topics are more popular in the other three journals studied in this paper.

• The Journal of the Korea Contents Association
• /
• v.20 no.9
• /
• pp.29-42
• /
• 2020

The purpose of this study is to present a qualitative research method for extracting and analyzing the comments written by YouTube video users. To do this, we used YouTube users' feedback to measure the hedonic, social, and utilitarian gratification of use and gratification theory(UGT) through by using analysis and topic modeling. The result of the measurement found that the first reason why users watch the trot singer, Cho Myung-sub's video in the KBS Korean broadcasting channel is to achieve hedonic gratification with high frequency. In word-document network analysis, the degree of centrality was high in words, such as 'cheering', 'thank you', 'fighting', and 'best'. Betweenness centrality is similar to the degree of centrality. Eigenvector centrality also shows that words such as 'love', 'heart', and 'thank you' are the most influential words of users' opinions. The results of the centrality analysis present that the majority of video users show their 'love', 'heart' and 'thank you' for the video. it indicates that the high words in centrality analysis is consistent with the high frequency words of hedonic and social gratification dimension of the UGT. The study has research methodological implication that shed light on the motivations for watching YouTube videos with UGT using text mining techniques that automate qualitative analysis, rather than following a survey-based structural equation model.

• The Journal of the Korea Contents Association
• /
• v.21 no.1
• /
• pp.92-104
• /
• 2021

This study aims to analyze online news articles to identify social issues related to patient safety and compare the changes in these issues before and after the implementation of the Patient Safety Act. This study performed text mining through the R program, wherein 7,600 online news articles were collected from January 1, 2010, to March 5, 2020, and examined using keyword analysis, topic modeling, and word co-occurrence network analysis. A total of 2,609 keywords were categorized into 8 topics: "medical practice", "medical personnel", "infection and facilities", "comprehensive nursing service", "medicine and medical supplies", "system development and establishment for improvement", "Patient Safety Act" and "healthcare accreditation". The study revealed that keywords such as "patient safety awareness", "infection control" and "healthcare accreditation" appeared before the implementation of the Patient Safety Act. Meanwhile, keywords such as "patient safety culture". and "administration and injection" appeared after the act's implementation with improved ranking of importance pertaining to nursing-related terminology. Interest in patient safety has increased in the medical community as well as among the public. In particular, nursing plays an important role in improving patient safety. Therefore, the recognition of patient safety as a core competency of nursing and the persistent education of the public are vital and inevitable.

• Journal of Internet Computing and Services
• /
• v.23 no.6
• /
• pp.79-86
• /
• 2022

This study aims to analyze the research trends on the civic participation in a smart city and to present implications to policy makers, industry professionals and researchers. As rapid urbanization is defining development trend of modern city, urban problems such as transportation, environment, and energy are spreading and intensifying around the city. Countries around the world are introducing smart cities to solve these urban problems and to achieve sustainable development. Recently, many countries are modifying urban planning from top-down to down-up by actively engaging citizens to participate in the urban construction process directly and indirectly. Although the construction of smart cities is being promoted in Korea to solve urban problems, awareness of smart cities and civic participation are low. In order to overcome this situation, discussions on ideas and methods that can increase civic participation in smart cities are continuously being conducted. Therefore, in this study, by collecting publication containing both 'Smart Cities' and 'Participation (Engagement)' in Scopus DB, the topics of related studies were categorized and research trends were analyzed using topic modeling. Through this study, it is expected that it can be used as evidence to understand the direction of civic participation research in smart cities and to present the direction of related research in the future.

• Journal of Korea Water Resources Association
• /
• v.55 no.spc1
• /
• pp.1235-1249
• /
• 2022

This study applied the web crawling technique for extracting big data news on water quality accidents in the water supply system and presented the algorithm in a procedural way to obtain accurate water quality accident news. In addition, in the case of a large-scale water quality accident, development patterns such as accident recognition, accident spread, accident response, and accident resolution appear according to the occurrence of an accident. That is, the analysis of the development of water quality accidents through key keywords and sentiment analysis for each stage was carried out in detail based on case studies, and the meanings were analyzed and derived. The proposed methodology was applied to the larval accident period of Incheon Metropolitan City in 2020 and analyzed. As a result, in a situation where the disclosure of information that directly affects consumers, such as water quality accidents, is restricted, the tone of news articles and media reports about water quality accidents with long-term damage in the event of an accident and the degree of consumer pride clearly change over time. could check This suggests the need to prepare consumer-centered policies to increase consumer positivity, although rapid restoration of facilities is very important for the development of water quality accidents from the supplier's point of view.

• Journal of The Korean Association For Science Education
• /
• v.44 no.3
• /
• pp.231-248
• /
• 2024

This study developed a chatbot for first-year high school students, employing open-source software and the Korean Sentence-BERT model for AI-powered document classification. The chatbot utilizes the Sentence-BERT model to find the six most similar Q&A pairs to a student's query and presents them in a carousel format. The initial dataset, built from online resources, was refined and expanded based on student feedback and usability throughout over the operational period. By the end of the 2023 academic year, the chatbot integrated a total of 30,819 datasets and recorded 3,457 student interactions. Analysis revealed students' inclination to use the chatbot when prompted by teachers during classes and primarily during self-study sessions after school, with an average of 2.1 to 2.2 inquiries per session, mostly via mobile phones. Text mining identified student input terms encompassing not only science-related queries but also aspects of school life such as assessment scope. Topic modeling using BERTopic, based on Sentence-BERT, categorized 88% of student questions into 35 topics, shedding light on common student interests. A year-end survey confirmed the efficacy of the carousel format and the chatbot's role in addressing curiosities beyond integrated science learning objectives. This study underscores the importance of developing chatbots tailored for student use in public education and highlights their educational potential through long-term usage analysis.

• 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.

• Journal of Internet of Things and Convergence
• /
• v.8 no.2
• /
• pp.41-48
• /
• 2022

This study tried to empirically explore which issues related to the social service agency for public(as below SSA), that is, social perceptions were formed, by using mess media related to the SSA. This study is meaningful in that it identifies the overall social perception and trend of SSA through public opinion. In order to extract media trend data, the search used the big data analysis system, Textom, to collect data from the representative portals Naver News and Daum News. The collected texts were 1,299 in 2020 and 1,410 in 2021, for a total of 2,709. As a result of the analysis, first, the most derived words in relation to the frequency of text appearance were 'SSA', 'establishment', and 'operation'. Second, as a result of the N-gram analysis, the pairs of words directly related to the SSA 'SSA and public', 'SSA and opening', 'SSA and launch', and 'SSA and Department Director', 'SSA and Staff', 'SSA and Caregiver' etc. Third, in the results of TF-IDF analysis and word network analysis, similar to the word occurrence frequency and N-gram results, 'establishment', 'operation', 'public', 'launch', 'provided', 'opened', ' 'Holding' and 'Care' were derived. Based on the above analysis results, it was suggested to strengthen the emergency care support group, to commercialize it in detail, and to stabilize jobs.

• Journal of the Korean Institute of Landscape Architecture
• /
• v.52 no.1
• /
• pp.34-45
• /
• 2024

Companion animals are increasingly being recognized as members of society in outdoor public spaces. However, the presence of dogs in cities has become a subject of conflict between pet owners and non-pet owners, causing problems in terms of hygiene and noise. This study was conducted to analyze public complaint data using the keywords 'dog,' 'pet,' and 'puppy' through text mining techniques to identify the causes of conflicts in outdoor public spaces related to dogs and to identify key issues. The main findings of the study are as follows. First, the majority of dog-related complaints were related to the use of outdoor public spaces. Second, different types of outdoor public spaces have different spatial issues. Third, there were a total of four topics of dog-related complaints: 'Requesting a dog playground', 'Raising safety issues related to animals', 'Using facilities other than dog-only areas', and 'Requesting increased park management and enforcement related to pet tickets'. This study analyzed the perceptions of citizens surrounding pets at a time when the creation and use of public spaces related to pets are expanding. In particular, it is significant in that it applied a new method of collecting public opinions by adopting complaint data that clearly presents problems and requests.

• KIPS Transactions on Software and Data Engineering
• /
• v.11 no.9
• /
• pp.381-390
• /
• 2022

Influenced by a culture that prefers non-face-to-face activity during the COVID-19 pandemic, chatbot usage is accelerating. Chatbots have been used for various purposes, not only for customer service in businesses and social conversations for fun but also for mental health. Chatbots are a platform where users can easily talk about their depressed moods because anonymity is guaranteed. However, most relevant research has been on social media data, especially Twitter data, and few studies have analyzed the commercially used chatbots data. In this study, we identified the characteristics of depressive discourse in user-chatbot interaction data by analyzing the chats, including the word 'depress,' using the topic modeling algorithm and the text-mining technique. Moreover, we compared its characteristics with those of the depressive moods in the Twitter data. Finally, we draw several design guidelines and suggest avenues for future research based on the study findings.