• 한국유기농업학회지
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• 제29권3호
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• pp.317-332
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• 2021

This study estimated the predictive onion yield through Stepwise regression of big data and weather variables by onion growing season. The economic feasibility of onion observations using big data was analyzed using estimated predictive data. The social welfare effect was estimated through the model of Harberger's triangle using onion yield prediction with big data and it without big data. Predicted yield using big data showed a deviation of -9.0% to 4.2%. As a result of estimating the social welfare effect, the average annual value was 23.3 billion won. The average annual value of social welfare effects if big data was not used was measured at 22.4 billion won. Therefore, it was estimated that the difference between the social welfare effect when the prediction using big data was used and when it was not was about 950 million won. When these results are applied to items other than onion items, the effect will be greater. It is judged that it can be used as basic data to prove the justification of the agricultural observation project. However, since the simple Harberger's triangle theory has the limitation of oversimplifying reality, it is necessary to evaluate the economic value through various methods such as measuring the effect of agricultural observation under a more realistic rational expectation hypothesis in future studies.

• 정보처리학회논문지:소프트웨어 및 데이터공학
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• 제3권12호
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• pp.553-564
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• 2014

본 논문은 지금까지의 소셜미디어 분석과 분석보고서 생성의 세 가지 문제점을 해결하기 위해서 소셜 빅데이터 마이닝에 기반한 이슈분석보고서 자동 생성 시스템을 제안한다. 세 가지 문제점은 분석의 고립성, 전문가의 주관성과 고비용에 기인한 정보의 폐쇄성이다. 시스템은 자연언어 질의분석, 이슈분석, 소셜 빅데이터 분석, 소셜 빅데이터 상관성분석과 자동 보고서 생성으로 구성된다. 생성된 보고서의 유용성을 평가하기 위해, 본 논문에서는 리커트척도를 사용하였고, 빅데이터 분석 전문가 2명이 평가하였다. 평가결과는 리커트 척도 평가에서 보고서의 품질이 비교적 유용하고 신뢰할 수 있는 것으로 평가되었다. 보고서 생성의 저비용, 소셜 빅데이터의 상관성 분석과 소셜 빅데이터 분석의 객관성 때문에, 제안된 시스템이 소셜 빅데이터 분석의 대중화를 선도할 것으로 기대된다.

• International Journal of Advanced Culture Technology
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• 제7권4호
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• pp.255-259
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• 2019

This study reviews the analysis and characteristics of databases from big data and then establishes representational strategy. Thus, analysis has continued for a long time in the quantity and quality of data, and there are changes in the location of data in the social sciences, past trends and the emergence of big data. The introduction of big data is presented as a prototype of new social science and is a useful practical example that empirically shows the need, basis, and direction of analysis through trend prediction services. Big data provides a future perspective as an important foundation for social change within the framework of basic social sciences.

• Asian Journal of Innovation and Policy
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• 제8권1호
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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.

• 대한안전경영과학회지
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• 제14권4호
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• pp.229-238
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• 2012

Within last 10 years, internet has become a daily activity, and humankind had to face the Data Deluge, a dramatic increase of digital data (Economist 2012). Due to exponential increase in amount of digital data, large scale data has become a big issue and hence the term 'big data' appeared. There is no official agreement in quantitative and detailed definition of the 'big data', but the meaning is expanding to its value and efficacy. Big data not only has the standardized personal information (internal) like customer information, but also has complex data of external, atypical, social, and real time data. Big data's technology has the concept that covers wide range technology, including 'data achievement, save/manage, analysis, and application'. To define the connected technology of 'big data', there are Big Table, Cassandra, Hadoop, MapReduce, Hbase, and NoSQL, and for the sub-techniques, Text Mining, Opinion Mining, Social Network Analysis, Cluster Analysis are gaining attention. The three features that 'bid data' needs to have is about creating large amounts of individual elements (high-resolution) to variety of high-frequency data. Big data has three defining features of volume, variety, and velocity, which is called the '3V'. There is increase in complexity as the 4th feature, and as all 4features are satisfied, it becomes more suitable to a 'big data'. In this study, we have looked at various reasons why companies need to impose 'big data', ways of application, and advanced cases of domestic and foreign applications. To correspond effectively to 'big data' revolution, paradigm shift in areas of data production, distribution, and consumption is needed, and insight of unfolding and preparing future business by considering the unpredictable market of technology, industry environment, and flow of social demand is desperately needed.

• 한국소프트웨어감정평가학회 논문지
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• 제17권1호
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• pp.59-66
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• 2021

Recently, conceptual information model is changing fast, and these changes are coming about as a result of individual tendency, social cultural, new circumstances and societal shifts within big data environment. Despite the data is growing more and more, now is the time to commit ourselves to the development of renewable, invaluable information of social/live commerce. Because we have problems with various insoluble data, we propose about deep learning prediction model-based object classification in social commerce of big data environment. Accordingly, it is an increased need of social commerce platform capable of handling high volumes of multiple items by users. Consequently, responding to rapid changes in users is a very significant by deep learning. Namely, promptly meet the needs of the times, and a widespread growth in big data environment with the goal of realizing in this paper.

• 문화기술의 융합
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• 제9권3호
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• pp.655-662
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• 2023

사회과학 분야에서 빅데이터 연구는 기존의 사회과학 연구방법을 보완하는 역할을 하고 있다. 사회과학자들이 선호하는 서베이 및 실험 방법이 주로 회상 기억에 의존하여 다소 부정확하다면 빅데이터는 실시간 기록이라 보다 정확하다. 기존의 사회과학 연구가 시간과 비용 등의 이유로 연구대상을 전수 조사하기보다 표집에 의한 표본 조사를 주로 하는 것과 달리 빅데이터 연구는 전수에 가까운 데이터를 분석한다. 그렇지만 시간의 흐름에 따라 사회 분위기가 변할 수 있고, 연구대상도 동일하지 않아 연구의 반복 및 재현은 둘 다 쉽지 않다. 무엇보다 기존의 사회과학 연구가 '이론-방법-데이터'의 삼각구조가 튼튼한 데 반해 빅데이터를 활용한 분석은 이론의 빈약함을 보이고 있어 심각한 문제다. 과학적 설명논리로서의 이론이 없으면 연구결과를 얻고서도 제대로 해석하지 못하거나 온전히 활용 할 수 없기 때문이다. 그러므로 빅데이터 연구가 진정한 방법론적 혁신이 되기 위해서는 새로운 이론(블랙박스)을 창출하기 위한 연구자들의 노력과 함께 빅 씽킹(big thinking)이 필요함을 제안했다.

• 한국콘텐츠학회논문지
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• 제20권1호
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• pp.142-151
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• 2020

우리는 이제 초연결사회(Hyper-Connectivity)에 살고 있다. 오늘날 대중이 소셜 커뮤니케이션을 적극적으로 활용하게 된 이유는 필요한 정보가 웹(Web) 공간을 통해서 소셜 빅데이터(Social Big Data)라는 이름으로 수집되고 분류되어 정보의 생태계인 빅데이터 시대를 만들어 가고 있기 때문이다. 빅데이터 정보가 대중에게 꼭 필요한 정보로 이용되기 위해서는 알기 쉽고 명확하게 전달할 수 있는 빅데이터 시각화작업이 필요하다. 본 연구는 소셜 빅데이터의 정보에 따른 시각화 유형을 분류하였고, 경험 평가대상으로 실제 빅데이터 시각화를 직접 활용하고 연구해야 하는 관련 전공생들과 일반인을 포함한 체험자를 대상으로 하였다. 체험자들의 경험을 분석한 결과, 데이터를 관리·분석·활용할 수 있는 시각화 전달방법에 대한 중요한 시사점이 도출되었다. 이에 따른 빅데이터 시각화 전략은 SNS상의 데이터 환경과 사용자의 눈높이에 맞는 방식으로 표현되어야 한다는 것이다. 앞으로 사용자를 위한 빅데이터 시각화가 상품서비스나 사회적 트렌드에 적용하여 활용된다면 개인의 상품 구매, 취향, 문화 등 그 역할과 적용 범위가 넓어지고 적용 대상이 많아질 것이라는 측면에서 중요한 자료가 될 것으로 생각한다.

• 한국정보시스템학회지:정보시스템연구
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• 제32권2호
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• pp.137-152
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• 2023

Purpose The purpose of this study is to analyze big data related to DURIBAL from the operation of taxis reserved for the disabled to identify the issues and suggest solutions. ESG management should be translated into "environmental factors, social responsibilities, and transparent management." Therefore, the current study used Big Data analysis to analyze the factors affecting the standby of taxis reserved for the disabled and relevant problems for implications on convenience of social weak. Design/methodology/approach The analysis method used R, Excel, Power BI, QGIS, and SPSS. We proposed several suggestions included problems with managing cancellation data, minimization of dark data, needs to develop an integrated database for scattered data, and system upgrades for additional analysis. Findings The results showed that the total duration of standby was 34 minutes 29 seconds. The reasons for cancellation data were mostly use of other modes of transportation or delayed arrival. The study suggests development of an integrated database for scattered data. Finally, follow-up studies may discuss government-initiated big data analysis to comparatively analyze the use of taxis reserved for the disabled nationwide for new social value.

• 인간식물환경학회지
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• 제22권5호
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• pp.455-466
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• 2019

This study was carried out to analyze trends in floral products and services through the big data analysis of various social networking services (SNSs) and then to provide objective marketing directions for the floricultural industry. To analyze the big data of SNSs, we used four analytical methods: Cotton Trend (Social Matrix), Naver Big Data Lab, Instagram Big Data Analysis, and YouTube Big Data Analysis. The results of the big data analysis showed that SNS users paid positive attention to flower one-day classes that can satisfy their needs for direct experiences. Consumers of floral products and services had their favorite designs in mind and purchased floral products very actively. The demand for flower items such as bouquets, wreaths, flower baskets, large bouquets, orchids, flower boxes, wedding bouquets, and potted plants was very high, and cut flowers such as roses, tulips, and freesia were most popular as of June 1, 2019. By gender of consumers, females (68%) purchased more flower products through SNSs than males (32%). Consumers preferred mobile devices (90%) for online access compared to personal computers (PCs; 10%) and frequently searched flower-related words from February to May for the past three years from 2016 to 2018. In the aspect of design, they preferred natural style to formal style. In conclusion, future marketing activities in the floricultural industry need to be focused on social networks based on the results of big data analysis of popular SNSs. Florists need to provide consumers with the floricultural products and services that meet the trends and to blend them with their own sensitivity. It is also needed to select SNS media suitable for each gender and age group and to apply effective marketing methods to each target.