• Journal of the Architectural Institute of Korea Planning & Design
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• 제35권2호
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• pp.139-146
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• 2019

The purpose of this study is to derive an improved method for analyzing old buildings with risk of collapse using public big data. Previous studies on the risk of building collapse focused on internal factors such as building age and structural vulnerability. However, this study suggests a method to derive potentially collapsible buildings considering not only internal factors of buildings but also external factors such as nearby new construction data. Based on the big data analysis, this study develops a system to visualize vulnerable buildings that require safety diagnosis and proposed a future utilization plan.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제17권11호
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• pp.2966-2986
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• 2023

Climate change is a constant threat to human life, and it is important to understand the public perception of this issue. Previous studies examining climate change have been based on limited survey data. In this study, the authors used big data such as news articles and social media data, within which the authors selected specific keywords related to climate change. Using these natural language data, topic modeling was performed for discourse analysis regarding climate change based on various topics. In addition, before applying topic modeling, sentiment analysis was adjusted to discover the differences between discourses on climate change. Through this approach, discourses of positive and negative tendencies were classified. As a result, it was possible to identify the tendency of each document by extracting key words for the classified discourse. This study aims to prove that topic modeling is a useful methodology for exploring discourse on platforms with big data. Moreover, the reliability of the study was increased by performing topic modeling in consideration of objective indicators (i.e., coherence score, perplexity). Theoretically, based on the social amplification of risk framework (SARF), this study demonstrates that the diffusion of the agenda of climate change in public news media leads to personal anxiety and fear on social media.

• Journal of the Korea Institute of Information and Communication Engineering
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• 제21권2호
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• pp.435-442
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• 2017

Our anxiousness has risen for recent increase in unpredicatable disaster. Accordingly, for the future society's preventing measure in advance against current considerable disasters due to societal crisis, we need to prepare secure measure ahead. Hence, we need to recognize the significance of governmental role and the value of Big Data application as ICT developed country in order to manage social crisis all the time. This manuscript analyzes human anxiety from listed disasters and describes that our government seeks new way to utilize Big Data in public in order to visualize Big Data related issues and its significance and urgency. Also, it suggests domestic/international application trend of Big Data's public sector with new practical approach to Big Data. Then, it emphasizes e-Gov's role for its Big Data application and suggests policies implying governmental use of Big Data for social crisis management by case-studying disaster measures against unpredictable crisis.

• Journal of KIBIM
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• 제13권3호
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• pp.39-47
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• 2023

This study aims to introduce a model for enhancing community well-being through the utilization of public open data. To objectively assess abstract notions of residential satisfaction, text data from complaints is analyzed. By leveraging accessible public data, costs related to data collection are minimized. Initially, relevant text data containing civic complaints is collected and refined by removing extraneous information. This processed data is then combined with meaningful datasets and subjected to topic modeling, a text mining technique. The insights derived are visualized using Geographic Information System (GIS) and Application Programming Interface (API) data. The efficacy of this analytical model was demonstrated in the Godeok/Gangil area. The proposed methodology allows for comprehensive analysis across time, space, and categories. This flexible approach involves incorporating specific public open data as needed, all within the overarching framework.

• Journal of Digital Convergence
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• 제17권2호
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• pp.195-200
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• 2019

Nowadays as the use of mobile communication devices such as smart phones and tablets and the use of Computer is expanded, data is being collected exponentially on the Internet. In addition, due to the development of SNS, users can freely communicate with each other and share information in various fields, so various opinions are accumulated in the from of big data. Accordingly, big data analysis techniques are being used to find out the difference between the response of the general public and the response of the media. In this paper, we analyzed the public response in SNS about child allowance and childbirth grant and analyzed the response of the media. Therefore we gathered articles and comments of users which were posted on Twitter for a certain period of time and crawling the news articles and applied sentiment analysis. From these data, we compared the opinion of the public posted on SNS with the response of the media expressed in news articles. As a result, we found that there is a different response to some national policy between the public and the media.

• Genomics & Informatics
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• 제17권4호
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• pp.44.1-44.3
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• 2019

Artificial intelligence (AI), big data, and ubiquitous robotic companions -the three most notable technologies of the 4th Industrial Revolution-are receiving renewed attention each day. Technologies that can be experienced in daily life, such as autonomous navigation, real-time translators, and voice recognition services, are already being commercialized in the field of information technology. In the biosciences field in Korea, such technologies have become known to the local public with the introduction of the AI doctor Watson in large number of hospitals. Additionally, AlphaFold, a technology resembling the AI AlphaGo for the game Go, has surpassed the limit on protein folding predictions-the most challenging problems in the field of protein biology. This report discusses the significance of AI technology and big data on the bioscience field. The introduction of automated robots in this field is not just only for the purpose of convenience but a prerequisite for the real sense of AI and the consequent accumulation of basic scientific knowledge.

• Journal of Korea Society of Digital Industry and Information Management
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• 제11권1호
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• pp.157-169
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• 2015

In digital marketing, means of public relations and marketing of enterprises are changing into marketing techniques of predictive analytics. A significant study can be carried out by an analysis of 'the patterns of customers' uses' using big data on major portal sites and SNSs and their correlation with related keywords. This study analyzes the origins of mythological characters in major brands such as Nike, Hermes, Versace, Canon and Starbucks. Also, it extracts related keywords and relevance using big data on portal sites and SNS and their correlation. Nike marketing that reminds people of 'the goddess of victory, Nike' formed a good combination of the brand with relevance. Most of them are based on Greek mythology and have rich materials for storytelling and artistic values in common. Hopefully, this case analysis of foreign brands would become a starting point of discovering the materials of the domestic mythological characters.

• Korea Trade Review
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• 제47권3호
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• pp.57-73
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• 2022

The process and change of convergence in the economy and industry with the development of digital technology and combining with new technologies is called Digital Transformation. Specifically, it refers to innovating existing businesses and services by utilizing information and communication technologies such as big data analysis, Internet of Things, cloud computing, and artificial intelligence. Digital transformation is changing the shape of business and has a wide impact on businesses and consumers in all industries. Among them, the big data and analytics market is emerging as one of the most important growth drivers of digital transformation. Integrating intelligent data into an existing business is one of the key tasks of digital transformation, and it is important to collect and monitor data and learn from the collected data in order to efficiently operate a data-based business. In developed countries overseas, research on new business models using various data accumulated at the level of government and private companies is being actively conducted. However, although the trade and import/export data collected in the domestic public sector is being accumulated in various types and ranges, the establishment of an analysis and utilization model is still in its infancy. Currently, we are living in an era of massive amounts of big data. We intend to discuss the value of trade big data possessed from the past to the present, and suggest a strategy to activate trade big data for trade digital transformation and a new direction for future trade big data research.

• Proceedings of the Korean Society of Computer Information Conference
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• 한국컴퓨터정보학회 2019년도 제59차 동계학술대회논문집 27권1호
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• pp.433-434
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• 2019

이 논문은 공공 빅 데이터를 활용하여 '서울자전거 따릉이'를 기반으로 자전거 교통 데이터베이스 시스템을 제작하고, 제작한 데이터베이스 시스템을 활용하는 예시를 보여주고 있습니다. 데이터베이스 시스템의 제작 과정을 통하여 데이터베이스 설계, 데이터 수집, 제작 및 가공 과정, 데이터베이스 시스템의 유용한 활용 예시를 확인할 수 있습니다. 버스, 택시와 같이 따릉이와 연계할 수 있는 다양한 대중교통 데이터를 추가로 활용한다면 더욱 정확하게 따릉이의 발전방향과 혼잡한 교통 환경 개선을 제시할 수 있는 유용한 정보를 도출할 수 있을 것이다.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 한국정보통신학회 2017년도 추계학술대회
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• pp.146-147
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• 2017

Big data analysis is a technique for effectively analyzing unstructured data such as the Internet, social network services, web documents generated in the mobile environment, e-mail, and social data, as well as well formed structured data in a database. The most big data analysis techniques are data mining, machine learning, natural language processing, and pattern recognition, which were used in existing statistics and computer science. Global research institutes have identified analysis of big data as the most noteworthy new technology since 2011. Therefore, companies in most industries are making efforts to create new value through the application of big data. In this study, we analyzed using the Social Matrics which a big data analysis tool of Daum communications. We analyzed public perceptions of "Internet of things" keyword, one month as of october 8, 2017. The results of the big data analysis are as follows. First, the 1st related search keyword of the keyword of the "Internet of things" has been found to be technology (995). This study suggests theoretical implications based on the results.