• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.12
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• pp.1880-1889
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• 2022

The online portal platform provides online news with online comments, but the anonymity of comments causes incivility, and online comments are considered social problems. While there are many foreign language-based incivility detection studies, in-depth research is not being conducted in Korea since there has not been implemented Korean language dataset which is labeled detailed criteria of incivility. In this study, the incivility notation of comments was conducted in a total of 13 items, uncivil words were summarized. Furthermore, Attention algorithm was applied to each comment and summary to extract embedding vectors. 2-d CNN followed at the end to detect incivility in given data. As a result, we showed that the proposed algorithm is useful for anti-citizen detection such as name-calling and offensive tones. This study is expected to contribute to the formation of a healthy online comment culture by detecting uncivil comments which hinder democratic discourse.

• Proceedings of the Korea Water Resources Association Conference
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• 2020.06a
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• pp.386-386
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• 2020

가뭄은 강수, 증발산, 대기온도, 토양수분 등 다양한 수문기상학적 인자들이 복합적으로 작용하여 발생되기 때문에 가뭄의 정확한 사상을 분석하는 것은 매우 어렵다. 또한 어떤 요인을 중심으로 고려하느냐에 따라 가뭄은 다양한 시각으로 정의되고 있다. 일정기간 평균 강수량보다 적은 강수로 인해 건조한 날이 지속되는 것, 즉 기상요소를 중심으로 가뭄을 정의하는 것을 기상학적 가뭄이라 하며, 작물의 생육에 필요한 수분을 중심으로 고려하는 것을 농업적 가뭄이라 한다. 또한 하천유량, 댐 저수량 등 전반적인 수자원 공급원의 부족을 수문학적 가뭄이라 한다. 이와 같이 다양하게 나타는 가뭄의 발생특성을 정량적으로 해석하기 위해 다양한 가뭄지수가 개발되어 왔다. 그러나 현재까지 개발된 가뭄지수들은 공통적으로 정형데이터를 활용하여 산정한다. 하지만 최근에는 비정형데이터를 활용하여 지수(Index)를 산정하거나, 재난관리에 적용하는 등 비정형 데이터의 활용이 급증하고 있다. 따라서 본 연구에서는 비정형 데이터(뉴스 데이터)를 활용하여 가뭄지수를 산정하고 기존의 가뭄지수들과의 상관성 분석을 실시 한 뒤, 지수결합을 통해 가뭄사상 분석의 새로운 방안을 제시하고자 하였다. 본 연구의 공간적범위는 2014~2015 충남서북부가뭄 지역 중 가장 큰 피해를 입었던 보령지역으로 선정하였으며 시간적범위는 2013~2016년으로 설정하였다. 비정형 데이터의 구축은 크롤링(Crawling)을 활용하여 네이버 뉴스의 기사를 수집하였으며 자료의 신뢰성을 위해 URL이 동일한 중복기사 및 '보령', '가뭄' 단어가 없는 기사는 제거하였다. 구축된 데이터를 기반으로 월별 빈도를 산출하고 표준점수(Z-score)로 환산하여 가뭄지수를 산정하였다. 산정된 가뭄지수가 어떤 가뭄의 유형(기상학적, 농업적, 수문학적)을 보이는지 확인하기 위해 기존의 가뭄지수들과 상관성분석을 실시하였으며, 가장 높은 상관성을 보이는 가뭄지수와 결합을 통해 새로운 가뭄 사상을 분석하였다. 본 연구에서 진행한 가뭄사상 분석은 향후 가뭄만이 아니라 다양한 재난분야에서 비정형 데이터를 활용한 분석의 기초로자료로 활용될 수 있을 것이다.

• The Journal of the Convergence on Culture Technology
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• v.9 no.4
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• pp.113-119
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• 2023

Despite the lifting of the mandatory wearing of masks, which was the main tool of the COVID-19 quarantine policy, we paid attention to the fact that some people are still wearing masks, and we wanted to clarify why people do not take off their masks. Through a survey in this regard, we were able to ascertain why some people continue to wear masks in a broader context. In this article, we directly and indirectly confirm the hidden side of citizens' continued wearing of masks by analyzing how the lifting of the mask-wearing obligation was reported in media articles that have a significant impact on citizens' behavior and attitude. Through this, it was confirmed that citizens continue to wear masks to protect themselves in an uncertain situation where the COVID-19 endemic has not been declared, despite the quarantine authorities' announcement of lifting the mandatory wearing. In a situation where crises such as COVID-19 are expected to repeat frequently in the future, it was concluded that it is important to build trust in the quarantine authorities.

• The Journal of the Korea Contents Association
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• v.22 no.8
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• pp.14-32
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• 2022

This study aims to examine the perception of false information and deepfakes according to the experience of being exposed to false information and deepfake images for YouTube content users. The study used the data from 'YouTube Use and False Information Exposure Experience' conducted by the Korea Press Foundation in 2018. For the statistical analysis, correspondent analysis was employed. The main results followed as: First, it was found that men who have been exposed to false information are most seriously aware of the problems caused by false information on YouTube. Second, regarding the need for regulation on deepfake images, women who have experienced exposure to deepfake images tended to agree, and women had a stronger awareness of the need for regulation due to damage to deepfake images than men. While YouTube users generally agree that regulation is necessary, it is required to educate YouTube users about the types of disinformation and deepfakes. In particular, it is considered to be desirable to create an environment for the self-regulation of the producers and distributors.

• International conference on construction engineering and project management
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• 2015.10a
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• pp.450-453
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• 2015

The Construction Engineering Industry (CEI) is construction field based on professional knowledge, staff and information service, and is distinguished by construction activity. The contemporary CEI market has extended globally and diversified construction work classifications. International construction engineering companies now have an important economic and social effect. Over the last five years (2009 to 2013), the top-200 global engineering firms reported global revenue that grew from 54.4 billion to 71.5 billion, about 27% growth (ENR, 2014). Countries such as the U.S.A., Canada, those in Europe (Several developed countries, i.e., United Kingdom, Netherlands, France, Spain, France, Italy, and Spain), Australia, Japan, China, and Korea comprise the bulk of world construction engineering revenue. Although the construction engineering market continues to grow, much of the work is limited to Europe, mid-Asia, and Asia. Additionally, specific construction types are focused on building projects, industrial plants, and refining plants. As such, there are imbalances in the construction engineering market and some market saturation. Further, there is heavy competition and the construction engineering market may shrink in the future. This paper analyzed various factors affecting the construction engineering market, specifically looking at construction classifications and factors related to a global market. To accomplish this, we collected to data from Engineering News Record (ENR) and recast each variable. And we used nonparametric statistics because the number of cases were small, making it difficult to assume a case's population parameter. Then we tested with the Kruskal-Wallis test and drew results. The results indicate that concentration in particular construction types and extending global regional markets will be have a positive effect on the overall global construction engineering market..

• Educational Technology International
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• v.11 no.2
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• pp.77-103
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• 2010

The purpose of this study was to develop an instructional model using new technologies aiming to secure students' learnability and to enhance the public school values in the rural districts. The present study attempts to suggest a practical e-learning instructional and learning model named Group Dynamics- based Debate Instructional Model', which utilizes unique technology environment conditions in most. To develop the model, concepts of group dynamics and debate-based instructional models were reviewed. And in-service teachers in two public schools in a certain rural district were interviewed in order to collect and analyze their needs for a teaching and learning model with which they utilizes unique technology conditions as environment in most. Based on literature review and the need analysis, a group dynamics-based debate instructional model has been suggested in terms of conceptual model. And then expert assessment composing of five in-service teachers from the model schools was implemented twice in order to acquire the suggested model validation, followed by the model validation by a group of experts. Then a revised group dynamics-based debate instructional model has been finally suggested. The group dynamics-based debate instructional model is expected to build up members' affective connection in the process, to generate group value, or collective intelligence, and to establish positive discussion culture. Furthermore, beyond of just utilizing the existing materials, learners are encouraged to develop and collect their own materials and data such as expert's interview, or public news for their argument or refutation. In doing so, learners enhance their learnability as well as accountability, prompting self-directed learning, and establishing appropriate discussion culture resulting in positive learning outcomes.

• Asia-Pacific Journal of Business
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• v.14 no.2
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• pp.119-139
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• 2023

Purpose - This study is the first field study about the insurance market in North Korea. By analysing the information and the data collected from the visit to North Korea, we introduced the most recent change on the insurance market in North Korea and analyzed the impact of the change of economic policy on the insurance market. This study may enhance the understanding the current situation and provide expectations on the future of the insurance market in North Korea. Design/methodology/approach - This study is based on the field study doen in 2018 to Pyeong Yang, the capital of North Korea, The most information was collected from the legal documents, news papers and academic reports. Findings - During his regime from the year of 2012, Kim Jong Eun, the Supreme Leader of North Korea, initiated the drastic change in economic renovation policy in North Korea by shifting the economic system from the commodity economy to the market economy. Due to the policy, the insurance market in North Korea became marginally privatized and the market of life insurance contracts is expected to be increased if North Korea may resolve the political conflicts between North Korea and the United States and its allies in Asia mainly due to its nuclear testing. Research implications or Originality - Until now, very few studies have been done regarding the financial market in North Korea, especially about the insurance market. Our study provides unique information on the insurance market in North Korea because all the information and its implications are based on the field study in 2018.

• The Journal of the Convergence on Culture Technology
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• v.10 no.3
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• pp.713-722
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• 2024

This study highlights the impact of Artificial Intelligence (AI) technology on journalism, discussing its utility and addressing major ethical concerns. Broadcasting companies and media institutions, such as the Bloomberg, Guardian, WSJ, WP, NYT, globally are utilizing AI for innovation in news production, data analysis, and content generation. Accordingly, the ecosystem of AI journalism will be analyzed in terms of scale, economic feasibility, diversity, and value enhancement of major media AI service types. Through the previous literature review, this study identifies key ethical and social issues in AI journalism as well. It aims to bridge societal and technological concerns by exploring mutual development directions for AI technology and the media industry. Additionally, it advocates for the necessity of integrated guidelines and advanced AI literacy through social consensus in addressing these issues.

• Journal of the Korean Society of Marine Environment & Safety
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• v.30 no.4
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• pp.299-307
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• 2024

Fishing villages, which are the focus of this study, are interested in fishing tourism for creating a new income base and sustaining fishing communities. This is because the extraordinary nature of the fishing village space creates new values in line with the function of tourism, however, the related policies are less than adequate compared to the importance of fishing village tourism. Therefore, this study aims to analyze the interest of Korean society in fishing village tourism the manner in which this issue has changed over time. Using the news analysis system, BigKinds, we systematically collected and analyzed articles related to fishing village tourism reported in the domestic media. The results showed that social interest in fishing village tourism and government policy support had increased over time, suggesting that fishing village tourism was an important strategy that could revitalize local economies and prevent the disappearance of fishing villages.

• Journal of Intelligence and Information Systems
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• v.24 no.3
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• pp.199-219
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• 2018

With the everyday use of the Internet and the spread of various smart devices, users have been able to communicate in real time and the existing communication style has changed. Due to the change of the information subject by the Internet, data became more massive and caused the very large information called big data. These Big Data are seen as a new opportunity to understand social issues. In particular, text mining explores patterns using unstructured text data to find meaningful information. Since text data exists in various places such as newspaper, book, and web, the amount of data is very diverse and large, so it is suitable for understanding social reality. In recent years, there has been an increasing number of attempts to analyze texts from web such as SNS and blogs where the public can communicate freely. It is recognized as a useful method to grasp public opinion immediately so it can be used for political, social and cultural issue research. Text mining has received much attention in order to investigate the public's reputation for candidates, and to predict the voting rate instead of the polling. This is because many people question the credibility of the survey. Also, People tend to refuse or reveal their real intention when they are asked to respond to the poll. This study collected comments from the largest Internet portal site in Korea and conducted research on the 19th Korean presidential election in 2017. We collected 226,447 comments from April 29, 2017 to May 7, 2017, which includes the prohibition period of public opinion polls just prior to the presidential election day. We analyzed frequencies, associative emotional words, topic emotions, and candidate voting rates. By frequency analysis, we identified the words that are the most important issues per day. Particularly, according to the result of the presidential debate, it was seen that the candidate who became an issue was located at the top of the frequency analysis. By the analysis of associative emotional words, we were able to identify issues most relevant to each candidate. The topic emotion analysis was used to identify each candidate's topic and to express the emotions of the public on the topics. Finally, we estimated the voting rate by combining the volume of comments and sentiment score. By doing above, we explored the issues for each candidate and predicted the voting rate. The analysis showed that news comments is an effective tool for tracking the issue of presidential candidates and for predicting the voting rate. Particularly, this study showed issues per day and quantitative index for sentiment. Also it predicted voting rate for each candidate and precisely matched the ranking of the top five candidates. Each candidate will be able to objectively grasp public opinion and reflect it to the election strategy. Candidates can use positive issues more actively on election strategies, and try to correct negative issues. Particularly, candidates should be aware that they can get severe damage to their reputation if they face a moral problem. Voters can objectively look at issues and public opinion about each candidate and make more informed decisions when voting. If they refer to the results of this study before voting, they will be able to see the opinions of the public from the Big Data, and vote for a candidate with a more objective perspective. If the candidates have a campaign with reference to Big Data Analysis, the public will be more active on the web, recognizing that their wants are being reflected. The way of expressing their political views can be done in various web places. This can contribute to the act of political participation by the people.