• 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

• The Journal of the Korea Contents Association
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• v.21 no.11
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• pp.20-29
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• 2021

This study aims to explore the issue of drones and crime in newspaper articles. BIG KINDS, an online news archive of the Korea Press Foundation, collected 1,213 newspaper articles that met the terms of "drone" and "crime" in 11 central and 28 regional comprehensive newspapers between January 1, 1990 and May 1, 2021. Among them, we perform keyword frequency, centrality analysis, network structure construction, CONCOR analysis, and density matrix analysis on 117 key keywords. According to the analysis, the main issues were classified into eight, and the report analysis on drones and crimes in newspaper articles showed that the government's policy-making and social problems on protecting people's privacy, preventing illegal filming, securing navigation safety, social security and resolution. This study attempts to expand the field of humanities and social studies related to drones and crime, and specifically suggests the current status and counterplan against drone-related crimes as policy implications and media implications.

• Proceedings of the Korea Water Resources Association Conference
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• 2022.05a
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• pp.378-378
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• 2022

상수도시스템의 과정 중 최종 단계인 급수단계에서 지역전반에 수질문제가 발생할 경우, 직간접적인 피해의 해결은 장기간 지속될 수 있다. 본 연구에서는 실시간 비정형정보의 빅데이터 분석을 통해 상수도시스템에서 수질사고 문제의 파급력과 2차 피해 등의 연결 관계 변화 추적을 위한 기초적 분석을 수행하였다. 과거 대규모 수질사고가 발생된 바 있는 인천광역시 유충발생 사고를 대상으로 뉴스 기사 웹크롤링 절차를 정립하고, 그 결과를 분석하였다. '인천 유충'이 최초 보도되었던 2020년 7월 13일 부터 이후 1년을 대상으로 네이버 통합검색에 의해 표출되는 뉴스기사를 웹크롤링하였으며, 프로그래밍을 통한 불용어 제거 및 관련성 검토를 통해 총 920건의 기사를 분석하였다. 수질사고의 전개양상에 따라 사고발생, 확산, 수습, 그리고 보상의 4단계로 임의 구분하여 분석하였다. 의미분석을 위한 토픽모델링 기법은 잠재 디리클레 할당(Latent Dirichlet Allocation, LDA) 방법을 적용하였으며, 긍부정 감정분석은 KNU 한국어 감성사전(KNU sentiment lexicon)을 활용하여 수행하였다. 토픽 모델링 결과, 사고 발생에서부터 확산, 수습, 보상의 단계에 맞춰 적절한 주제어의 조합에 따른 기사들이 도출되었으며, 단계별 긍부정 기사 비율역시 사고의 전개단계에 따라 적절히 나타남을 확인하였다. 제시된 수질사고 관련 비정형정보 분석 방법론과 결과는 과거 사고 사례 분석을 통한 검색 및 긍부정 키워드 확정, 키워드 발생 비율 변동(사고전과 후)에 따른 상황판단 기준설정 등에 활용이 가능하다.

• Journal of the Korean Society of Clothing and Textiles
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• v.47 no.5
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• pp.779-803
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• 2023

The growth of digital news media and the stock price index has resulted in economic fluctuations in the fashion industry. This study examines the impact of fashion industry news and macroeconomic changes on the Textile & Wearing Apparel KOSPI over the past five years. An auto-regressive integrated moving average exogenous time series model was conducted using the fashion industry stock market index, the news topic index, and macro-economic indicators. The results indicated the topics of "Cosmetic business expansion" and "Digital innovation" impacted the Textile & Wearing Apparel KOSPI after one week, and the topics of "Pop-up store," "Entry into the Chinese fashion market," and "Fashion week and trade show" affected it after two weeks. Moreover, the topics of "Cosmetic business expansion" and "Entry into the Chinese fashion market" were statistically significant in the macroeconomic environment. Regarding the effect relation of Textile & Wearing Apparel KOSPI, "Cosmetic business expansion," "Entry into the Chinese fashion market," and consumer price fluctuation showed negative effects, while the private consumption change rate, producer price fluctuation, and unemployment change rate had positive effects. This study analyzes the impact of media framing on fashion industry business cycles and provides practical insights into managing stock market risk for fashion companies.

• Journal of Korea Port Economic Association
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• v.37 no.1
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• pp.159-178
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• 2021

This study analyzed issues and trends related to ports with 86,611 news articles for the 30 years from 1991 to 2020, using BIGKinds, a big data news analysis service. The analysis was based on keyword analysis, word cloud, relationship diagram analysis offered by BIG Kinds. Analysis results of issues and trends on ports for the last 30 years are summarized as follows. First, during Phase 1 (1991-2000), individual ports such as Busan, Incheon, and Gwangyang ports tried to strengthen their own competitiveness. During Phase 2 (2001-2010), efforts were made on gaining more professional and specialized port management abilities by establishing the Busan Port Authority in 2004, the Incheon Port Authority in 2005, and the Ulsan Port Authority in 2007. During Phase 3 (2011-2020), the promotion of future-oriented, eco-friendly, and smart ports was major issues. Efforts to reduce particulate matters and pollutants produced from ports were accelerated, and an attempt to build a smart port driven by port automation and digitalization was also intensified. Lastly, in 2020, when the maritime sector was severely hit by the unexpected shock of the COVID-19 pandemic, a microscopic analysis of trends and issues in 2019 and 2020 was made to look into the impact the pandemic on the maritime industry. It was found that shipping and port industries experienced more drastic changes than ever while trying to prepare for a post-pandemic era as well as promoting future-oriented ports. This study made policy suggestions by analyzing port-related news articles and trends, and it is expected that based on the findings of this research, further studies on enhancing the competitiveness of ports and devising a sustainable development strategy will follow through a comparative analysis of port issues of different countries, thereby making further progress toward academic research on ports.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.41 no.3
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• pp.154-161
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• 2018

This study conducted to predict the stock market prices based on the assumption that internet news articles might have an impact and effect on the rise and fall of stock market prices. The internet news articles were tested to evaluate the accuracy by comparing predicted values of the actual stock index and the forecasting models of the companies. This paper collected stock news from the internet, and analyzed and identified the relationship with the stock price index. Since the internet news contents consist mainly of unstructured texts, this study used text mining technique and multiple regression analysis technique to analyze news articles. A company H as a representative automobile manufacturing company was selected, and prediction models for the stock price index of company H was presented. Thus two prediction models for forecasting the upturn and decline of H stock index is derived and presented. Among the two prediction models, the error value of the prediction model (1) is low, and so the prediction performance of the model (1) is relatively better than that of the prediction model (2). As the further research, if the contents of this study are supplemented by real artificial intelligent investment decision system and applied to real investment, more practical research results will be able to be developed.

• Journal of the Korea Convergence Society
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• v.10 no.7
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• pp.191-198
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• 2019

This paper investigates different types of leadership found in foreign coaches in charge of the Korean national soccer team. To that end, news articles published during the tenure of those coaches were crawled for analysis. The analysis highlighted the following results. First, successful sports leaders showed their own specific types of leadership. Second, failed sports leaders showed specific types of leadership. The findings have the following implications. The leadership established based on the analysis results have practical implications in that they suggest the types of effectiveness leadership that are required of sports leaders in managing and leading athletes whilst generating tangible results and performance.

• Journal of Korea Society of Digital Industry and Information Management
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• v.19 no.1
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• pp.139-151
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• 2023

This study aims to gain insights into ChatGPT, which has recently received significant attention. The study utilized a mixed method involving case studies and news big data analysis. ChatGPT can be described as an optimized language model for dialogue. The question arises whether ChatGPT will replace Google search services, posing a potential threat to Google. It could hurt Google's advertising business, which is the foundation of its profits. With AI-based chatbots like ChatGPT likely to disrupt the web search industry, Google is establishing a new AI strategy. The study used the BIG KINDS service and analyzed 2,136 articles over six months, from August 23, 2022, to February 22, 2023. Thirty of these articles were written in 2022, while 2,106 have been reported recently as of February 22, 2023. Also, the study examined the contents of ChatGPT by utilizing literature research, news big data analysis, and use cases. Despite limitations such as the potential for false information, analyzing news big data and use cases suggests that ChatGPT is worth using.

• The Journal of Information Systems
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• v.32 no.2
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• pp.87-108
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• 2023

Purpose The main purpose of this study is to improve fake news detection performance by using video information to overcome the limitations of extant text- and image-oriented studies that do not reflect the latest news consumption trend. Design/methodology/approach This study collected video clips and related information including news scripts, speakers' facial expression, and video metadata from YouTube to develop fake news detection model. Based on the collected data, seven combinations of related information (i.e. scripts, video metadata, facial expression, scripts and video metadata, scripts and facial expression, and scripts, video metadata, and facial expression) were used as an input for taining and evaluation. The input data was analyzed using six models such as support vector machine and deep neural network. The area under the curve(AUC) was used to evaluate the performance of classification model. Findings The results showed that the ACU and accuracy values of three features combination (scripts, video metadata, and facial expression) were the highest in logistic regression, naïve bayes, and deep neural network models. This result implied that the fake news detection could be improved by using video information(video metadata and facial expression). Sample size of this study was relatively small. The generalizablity of the results would be enhanced with a larger sample size.

• The Journal of the Korea Contents Association
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• v.20 no.3
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• pp.515-526
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• 2020

Digital healthcare is a combined area of medical field and IT and various information on digital healthcare is provided in social media. This study aims to find the research trend of digital healthcare by collecting and analyzing data related to digital healthcare through the social media. The data were collected from Naver and Daum's news and blogs from January 2008 to June 2019. Major keywords with high frequency were extracted and visualized with wordcloud and network analysis was used to analyze the relationship between major keywords. Research combining medical field and IT from 2008 to 2001, various convergence research based on medical field and IT from 2012 to 2015, convergence research that applied the 4th industrial revolution technologies such as big data, blockchain and AI were actively conducted from 2016 to June 2019.