• 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.

• 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.

• International Journal of Internet, Broadcasting and Communication
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• 제15권3호
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• pp.211-218
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• 2023

Due to the implementation of COVID-19 distancing, interest and users in 'home training' are rapidly increasing. Therefore, the purpose of this study is to identify the perception of 'home training' through big data analysis on social media channels and provide basic data to related business sector. Social media channels collected big data from various news and social content provided on Naver and Google sites. Data for three years from March 22, 2020 were collected based on the time when COVID-19 distancing was implemented in Korea. The collected data included 4,000 Naver blogs, 2,673 news, 4,000 cafes, 3,989 knowledge IN, and 953 Google channel news. These data analyzed TF and TF-IDF through text mining, and through this, semantic network analysis was conducted on 70 keywords, big data analysis programs such as Textom and Ucinet were used for social big data analysis, and NetDraw was used for visualization. As a result of text mining analysis, 'home training' was found the most frequently in relation to TF with 4,045 times. The next order is 'exercise', 'Homt', 'house', 'apparatus', 'recommendation', and 'diet'. Regarding TF-IDF, the main keywords are 'exercise', 'apparatus', 'home', 'house', 'diet', 'recommendation', and 'mat'. Based on these results, 70 keywords with high frequency were extracted, and then semantic indicators and centrality analysis were conducted. Finally, through CONCOR analysis, it was clustered into 'purchase cluster', 'equipment cluster', 'diet cluster', and 'execute method cluster'. For the results of these four clusters, basic data on the 'home training' business sector were presented based on consumers' main perception of 'home training' and analysis of the meaning network.

• 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.

• 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.

• 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.

• 아태비즈니스연구
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• 제12권2호
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• pp.161-174
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• 2021

Purpose - The purpose of this study was to examine the recent popular consumption trend, the hocance phenomenon, using social media big data. The study intended to present practical directions and marketing measures for the recovery and growth of the hotel industry after COVID-19 pandemic. Design/methodology/approach - Big data analysis has been used in various fields, and in this study, it was used to understand the hocance phenomenon. For three years from January 1, 2018 to December 31, 2020, we collected text data including the keyword 'hocance' from the blog and cafe of NAVER and Daum. TEXTOM and UCINET 6 were used to collect and analyze the data. Findings - According to the results of analysis, the words such as 'hocance', 'hotel', 'Seoul', 'travel', 'swimming pool', 'Incheon', 'breakfast', 'child' and 'friend' were identified with high frequency. The results of CONCOR analysis showed similar results in all three years. It has been confirmed that 'swimming pool', 'breakfast', 'child' and 'friend' are important when deciding on the hocance package. Research implications or Originality - The study was differentiated in that it used social media big data instead of traditional research methods. Furthermore, it reflected social phenomena as a consumption trend so there was practical value in establishing marketing strategies for the tourism and hotel industry.

• 한국멀티미디어학회논문지
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• 제24권8호
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• pp.1192-1201
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• 2021

This study focused on how to analyze the ICT policy formation process using social big data. Specifically, in this study, a method for quantifying variables that influenced policy formation using the concept of a policy triggering mechanism and elements necessary to present the analysis results were proposed. For the analysis of the ICT policy triggering mechanism, variables such as 'Scope', 'Duration', 'Interactivity', 'Diversity', 'Attention', 'Preference', 'Transmutability' were proposed. In addition, 'interpretation of results according to data level', 'presentation of differences between collection and analysis time points', and 'setting of garbage level' were suggested as elements necessary to present the analysis results.

• 한국정보통신학회:학술대회논문집
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• 한국정보통신학회 2017년도 추계학술대회
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• pp.146-147
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• 2017

빅데이터 분석은 데이터베이스에 잘 정리된 정형 데이터뿐만 아니라 인터넷, 소셜 네트워크 서비스, 모바일 환경에서 생성되는 웹 문서, 이메일, 소셜 데이터 등 비정형 데이터를 효과적으로 분석하는 기술을 말한다. 대부분의 빅데이터 분석 기술 방법들은 기존 통계학과 전산학에서 사용되던 데이터 마이닝, 기계 학습, 자연 언어 처리, 패턴 인식 등이 이에 해당된다. 글로벌 리서치 기관들은 빅데이터 분석을 2011년 이래로 가장 주목받는 신기술로 지목해오고 있다. 따라서 대부분의 산업에서 기업들은 빅데이터의 적용을 통해 새로운 가치 창출을 위해 노력을 하고 있다. 본 연구에서는 다음 커뮤니케이션의 빅데이터 분석 도구인 소셜 매트릭스를 활용하여 분석하였다. 2017년 10월 8일 시점 1개월 기간을 설정하여 "사물인터넷" 키워드에 대한 대중들의 인식을 분석하였다. 빅데이터 분석의 결과는 다음과 같다. 첫째, 사물인터넷 키워드에 대한 1위 연관 검색어는 기술(995)인 것으로 나타났다. 결과를 바탕으로 연구의 한계와 시사점을 제시하고자 한다.