• Proceedings of the Korean Institute of Building Construction Conference
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• 2017.05a
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• pp.93-94
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• 2017

This study have derived the big issue of overseas construction through big data analysis. For identification of big issues on overseas construction, domestic online articles, 30 daily newspapers like the JoongAng Ilbo, 7 construction related articles including construction economy and 1,759 local newspapers and small media companies were analyzed from October 1st, 2015 to September 30th, 2016. 13,884 cases in total were used for big data analyses and big issue candidates were identified. The analysis result is as shown below. First, looking into major issues on overseas construction for a year, construction orders in the Middle East decreased because of the drop in oil prices. Accordingly, there were discussions on concerns and crises we may face as profitabilities worsened in overseas construction. Second, analyzing main concern based on 8 key words on overseas construction among construction issues for the last one year, it was found as following: Region (29.4%), Business environment (21.4%), Group (15.8%), Profitability (14.5%), Policy and Institution (7.8%), Market environment (4.2%), Business (project) (4.15%), and Education (3.2%). Third, among 30 issues on 8 key words, 10 key issues that are likely to spread and continue were identified. Then, a semantic network map among key words and centrality were analyzed.

• Korean Journal of Construction Engineering and Management
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• v.19 no.3
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• pp.89-96
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• 2018

This study derived big issues in overseas construction through big data analysis. To derive big issues in overseas construction, candidate groups of big issues were identified through big data analysis targeting 53,759 issues including 39,436 issues from major portal sites, 10,387 issues from daily newspapers, and 336 issues in construction magazines from Oct. 1, 2016 to Sep. 30, 2017. The main results are as follows: First, the main issues of overseas construction for the past one year showed that markets were concentrated in Middle East Asia and most of them were low-price order plant projects, which revealed the limitations. Although orders of overseas construction were slightly upward in the first half of 2017 compared to previous year, overseas construction orders are still unstable due to uncertainties in the international affairs and drops in oil prices. Second, the interest topics based on the 8th core keywords of overseas construction among the overseas construction issues for the past one year showed that region (29.9%), corporation environment (22.0%), profitability (17.0%), organizations (15.1%), projects (5.2%), market environment (3.6%), policy and system (3.6%), and education (3.5%) in the order of interest. Third, 10 core issues that have expandability and persistence of discourse were extracted out of 30 issue candidates with regard to eight keywords. Based on the extracted issues, detailed analysis on each of the core issues in overseas construction and correlation analysis between 10 core issues were conducted.

• The Journal of the Korea Contents Association
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• v.18 no.10
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• pp.229-235
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• 2018

The purpose of this study is to propose a method to utilize Big Data Analysis to find policy issues of local governments in the reality that utilization of big data becomes increasingly important in efficient and effective policy making process. For this purpose, this study analyzed the 180,000 articles of Suwon city for the past three years and identified policy issues and evaluated policy priorities through IPA analysis. The results of this study showed that the analysis of semi-formal big data through newspaper articles is effective in deriving the differentiated policy issues of different local autonomous bodies from the main issues in the nation, In this way, the methodology of finding policy issues through the analysis of big data suggested in this study means that local governments can effectively identify policy issues and effectively identify the people. In addition, the methodology proposed in this study is expected to be applicable to the policy issues through the analysis of various semi - formal and informal big data such as online civil complaint data of the local government, resident SNS.

• Asian Journal of Innovation and Policy
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• v.8 no.1
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• pp.58-72
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• 2019

The wave of the 4th Industrial Revolution was announced by Schwab Klaus at the 2016 World Economic Forum in Davos, and prospects and measures with the future society in mind have been put in place. With the launch of the Moon Jae-in administration in May 2017, Korea has shifted all of its interest to Big Data, which is one of the most important features of the 4th Industrial Revolution. In this regard, this study focuses on the role of the public sector, explores related issues, and identifies an agenda for determining the demand for ways to foster Big Data ecosystem, from an objective perspective. Furthermore, this study seeks to establish priorities for key Big Data issues from various areas based on importance and urgency using a Delphi analysis. It also specifies the agenda by which Korea should exert national and social efforts based on these priorities in order to demonstrate the role of the public sector in reinforcing the Big Data ecosystem.

• Journal of the Korean BIBLIA Society for library and Information Science
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• v.24 no.4
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• pp.53-73
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• 2013

This study revisits issues for Big data. Three research questions, understanding the concept of Big data, important issues of Big data research and utilization methods for library information services, are explored by the literature and practice reviews. Study results revealed several important issues of Big data including the concept in the context of real world situation, the problems with the accuracy and reliability of the data, privacy and ethical issues, and issues of intellectual property rights. With understanding these issues, a few utilization methods were introduced for Library and Information services. It was included using its analysis for developing vision, adopting Library management, supporting community services, and providing customized information services for various users. The study concluded Big data analysis would effectively provide valid evidences for all those services.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.34 no.6
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• pp.579-589
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• 2016

This research focuses on accomplishing analysis problems and issues by examining the policies and systems related to geo-spatial big data which have recently arisen, and suggests political and systemic improvement plan for service activation. To do this, problems and probable issues concerning geo-spatial big data service activation should be analyzed through the examination of precedent studies, policies and planning, pilot projects, the current legislative situation regarding geo-spatial big data, both domestic and abroad. Therefore, eight political and systematical improvement plan proposals are suggested for geo-spatial big data service activation: legislative-related issues regarding geo-spatial big data, establishing an exclusive organization in charge of geospatial big data, setting up systems for cooperative governance, establishing subsequent systems, preparing non-identifying standards for personal information, providing measures for activating civil information, data standardization on geo-spatial big data analysis, developing analysis techniques for geo-spatial big data, etc. Consistent governmental problem-solving approaches should be required to make these suggestions effectively proceed.

• Journal of Information Technology Services
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• v.11 no.4
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• pp.277-294
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• 2012

The purpose of this research is to analyze big data structure and various objects in big data industry based on ecological perspective. Big data is rapidly emerging as a highly valuable resource to secure competitiveness of enterprise and government. Accordingly, the main issues in big data are to find ways of creating economic value and solving various problems. However big data is not systematically organized, and hard to utilize as it constantly expands to related industry such as telecommunications, finance and manufacturing. Under this circumstance, it is crucial to understand range of big data industry and to which stakeholders are related. The ecological approach is useful to understand comprehensive industry structure. Therefore this study aims at confirming big data structure and finding issues from interaction among objects. Results of this study show main framework of big data ecosystem including relationship among object elements composing of the ecosystem. This study has significance as an initial study on big data ecosystem. The results of the study can be useful guidelines to the government for making systemized big data ecosystem and the entrepreneur who is considering launching big data business.

• Journal of the Korean Society of Safety
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• v.31 no.6
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• pp.121-128
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• 2016

Social Media transformed the mass media based information traffic, and it has become a key resource for finding value in enterprises and public institutions. Particularly, in regards to disaster management, the necessity for public participation policy development through the use of social media is emphasized. National Disaster Management Research Institute developed the Social Big Board, which is a system that monitors social Big Data in real time for purposes of implementing social media disaster management. Social Big Board collects a daily average of 36 million tweets in Korean in real time and automatically filters disaster safety related tweets. The filtered tweets are then automatically categorized into 71 disaster safety types. This real time tweet monitoring system provides various information and insights based on the tweets, such as disaster issues, tweet frequency by region, original tweets, etc. The purpose of using this system is to take advantage of the potential benefits of social media in relations to disaster management. It is a first step towards disaster management that communicates with the people that allows us to hear the voice of the people concerning disaster issues and also understand their emotions at the same time. In this paper, Korean language text mining based Social Big Board will be briefly introduced, and disaster issue detection model, which is key algorithms, will be described. Disaster issues are divided into two categories: potential issues, which refers to abnormal signs prior to disaster events, and occurrence issues, which is a notification of disaster events. The detection models of these two categories are defined and the performance of the models are compared and evaluated.

• Korean Journal of Agricultural Science
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• v.46 no.4
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• pp.955-969
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• 2019

Analyzing on-line consumer responses is directly related to the management performance of food companies. Therefore, this study collected and analyzed data from an on-line portal site created by consumers about food companies with issues and examined the relationships between the data and the management performance. Through this process, we identified consumers' awareness of these companies obtained from big data analysis and analyzed the relationship between the results and the sales and stock prices of the companies through a time-series graph and correlation analysis. The results of this study were as follows. First, the result of the text mining analysis suggests that consumers respond more sensitively to negative issues than to positive issues. Second, the emotional analysis showed that companies' ethics issues (Enterprise 3 and 4) have a higher level of emotional continuity than that of food safety issues. It can be interpreted that the problem of ethical management has great influence on consumers' purchasing behavior. Finally, In the case of all negative food issues, the number of word frequency and emotional scores showed opposite trends. As a result of the correlation analysis, there was a correlation between word frequency and stock price in the case of all negative food issues and also between emotional scores and stock price. Recently, studies using big data analytics have been conducted in various fields. Therefore, based on this research, it is expected that studies using big data analytics will be done in the agricultural field.

• Informatization Policy
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• v.23 no.1
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• pp.3-19
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• 2016

The purpose of the study is to analyze the existing literature and to suggest future research directions in the big data security area. This study identifies 62 research articles and analyses their publication year, publication media, general research approach, specific research method, and research topic. According to the results of the analyses, big data security research is at its intial stage in which non-empirical studies and research dealing with technical issues are dominant. From the research topic perspective, the area demonstrates the signs of initial research stage in which proportion of the macro studies dealing with overall issues is far higher than the micro ones covering specific implementation methods and sectoral issues. A few promising topics for future research include overarching framework on big data security, big data security methods for different industries, and government policies on big data security. Currently, the big data security area does not have sufficient research results. In the future, studies covering various topics in big data security from multiple perspectives are anticipated.