• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2016.10a
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• pp.124-125
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• 2016

빅데이터 분석은 기존 데이터베이스 관리 도구로부터 데이터를 수집, 저장, 관리, 분석할 수 있는 역량을 말한다. 또한 대량의 정형 또는 비정형 데이터 집합으로부터 가치를 추출하고 결과를 분석하는 기술을 의미한다. 대부분의 빅데이터 분석 기술 방법들은 기존 통계학과 전산학에서 사용되던 데이터 마이닝, 기계 학습, 자연 언어 처리, 패턴 인식 등이 해당된다. 글로벌 리서치 기관들은 빅데이터를 2011년 이래로 최근 가장 주목받는 신기술로 지목해오고 있다. 따라서 대부분의 산업에서 기업들은 빅데이터의 적용을 통해 가치 창출을 위한 노력을 기울이고 있다. 본 연구에서는 다음 커뮤니케이션의 빅데이터 분석도구인 소셜 매트릭스를 활용하여 키워드 분석을 통해 콜라겐 키워드에 대한 의미를 분석하고자 한다. 또한 분석결과를 바탕으로 실무적 시사점을 제시하고자 한다.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2014.10a
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• pp.671-672
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• 2014

최근 기업의 효율적인 경영을 위해 다양한 소셜 채널에서 폭발적으로 생성되고 확산되는 빅 데이터를 실시간으로 분석하는 기술이 개발되고 있다. 본 논문에서는 관광서비스에 관해 소셜 미디어 상의 빅 데이터를 이용하여 보다 정확하고 효율적인 정보 수집과 분석이 가능하도록 하기위한 모델구축 방법을 제안하고 관광서비스에 관한 평판을 분석한다. 관광 산업 도메인 네트워크를 활용한 표준화, 일반화 확보를 위해 먼저 B2C 산업군 및 업종별 공통 수집원 추출 및 표준화 분석 체계 수립을 통한 해당 적용분야의 설계안 수립하고 관광객(소비자) 작성 게시글 분석을 위한 산업군 정보 추출하며 관광지, 숙박지, 교통 등 다양한 업종에 대한 분석 수행한다. 관광지에 대한 평가 기준을 기존의 설문이 아닌 SNS 상의 고객 의견을 바탕으로 호감도로 분석한다.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2019.05a
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• pp.165-166
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• 2019

Big data analysis is the ability to collect, store, manage and analyze data from existing database management tools. Big data refers to large scale data that is generated in a digital environment, is large in size, has a short generation cycle, and includes not only numeric data but also text and image data. Big data is data that is difficult to manage and analyze in the conventional way. It has huge size, various types, fast generation and velocity. Therefore, companies in most industries are making efforts to create value through the application of Big data. In this study, we analyzed the meaning of keyword using Social Matrix, a big data analysis tool of Daum communications. Also, the theoretical implications are presented based on the analysis results.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.17 no.10
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• pp.2439-2446
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• 2013

Recently, SNS (Social Network Service) such as Twitter and Facebook has grown dramatically because of smart phones. Since development of IT has created massive information, social big data extremely increased. Competition between corporations is getting more intense, so they need customer feedback in order to fulfill an effective management. Because social big data plays an important role for getting customer feedback, a lot of corporations are interested in analyzing and applying of social big data. Collecting and analyzing social big data is operated by Buzz monitoring system. This paper demonstrates the research of buzz monitoring system that analyzes big data, and presents examples of customer reputation using buzz monitoring. In the paper, after all, it would analyze the result from the customer reputation, and research the implication.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2018.10a
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• pp.93-96
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• 2018

Big datatics technology that can store and analyze data and obtain new knowledge has been adjusted for importance in many fields of the society. Big data is emerging as an important problem in the field of information and communication technology, but the mind of continuous technology is rising. R, a tool that can analyze big data, is a language and environment that enables information analysis of statistical bases. In this thesis, we use this to analyze the Bible data. R is used to investigate the frequency of what text is distributed and analyze the Bible through analysis of social network.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2017.05a
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• pp.361-363
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• 2017

최근 소셜 미디어의 이용률이 폭발적으로 증가함에 따라, 방대한 데이터가 네트워크로 쏟아져 나오고 있다. 이들 데이터는 기존의 정형 데이터뿐만 아니라 이미지, 동영상 등의 비정형 데이터가 있으며, 이들을 포괄하여 빅데이터라고 불린다. 이러한 빅데이터는 오피니언 마이닝, 테스트 마이닝 등의 기술적인 분석 기법과 빅데이터 요약 및 효과적인 표현방법에 대한 시각화 기법에 대하여 활발한 연구가 이루어지고 있다. 이 논문은 인기 있는 사회연결망 서비스인 Twitter의 트윗을 수집하고, 빅데이터 분석 기법인 텍스트 마이닝을 활용하여 2017년 대선에 대하여 분석하였다. 또한 분석된 자료의 효과적인 전달을 위해 워드 클라우드 진행하였다. 이 논문을 위하여 인기 있는 SNS인 Twitter의 최근 7일간 트윗(tweet)을 수집하고 분석하였다.

• The Journal of the Korea Contents Association
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• v.13 no.2
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• pp.211-219
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• 2013

The analysis method using Big Data has evolved based on the Big data Management Technology. There are quite a few researching institutions anticipating new era in data analysis using Big Data and IT vendors has been sided with them launching standardized technologies for Big Data management technologies. Big Data is also affected by improvements of IT gadgets IT environment. Foreran by social media, analyzing method of unstructured data is being developed focusing on diversity of analyzing method, anticipation and optimization. In the past, data analyzing methods were confined to the optimization of structured data through data mining, OLAP, statics analysis. This data analysis was solely used for decision making for Chief Officers. In the new era of data analysis, however, are evolutions in various aspects of technologies; the diversity in analyzing method using new paradigm and the new data analysis experts and so forth. In addition, new patterns of data analysis will be found with the development of high performance computing environment and Big Data management techniques. Accordingly, this paper is dedicated to define the possible analyzing method of social media using Big Data. this paper is proposed practical use analysis for social media analysis through data mining analysis methodology.

• Proceedings of the Korea Information Processing Society Conference
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• 2017.11a
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• pp.48-51
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• 2017

빅데이터는 저장되지 않았거나 저장되더라도 분석되지 못하고 버리게 되는 방대한 양의 데이터를 말한다. 실제로도 빅데이터는 페이스북, 트위터등의 소셜 네트워크에서 많이 발생하고 있는데, 이러한 방대한 데이터들을 어떻게 효율적으로 저장하고 분석하는지에 대한 관심이 많아지고 있다. 따라서 본 논문에서는 빅데이터의 개념, 빅데이터의 향후 동향과 이슈들에 대해 살펴보고, 빅데이터 시스템이 데이터를 수집하고 저장하는 것에 대한 고려할만한 사항들과 효율적인 해결방안에 대해 제시하였다.

• The Journal of the Korea Contents Association
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• v.19 no.6
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• pp.10-23
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• 2019

Although social big data can provide a multi-faceted perspective on school bullying experiences among children and adolescents, the complexity and variety of unstructured text presents a challenge for systematic collection and analysis of the data. Development of an ontology, which identifies key terms and their intricate relationships, is crucial for extracting key concepts and effectively collecting data. The current study elaborated on the definition of an ontology, carefully described the 7 stage development process, and applied the ontology for collecting and analyzing school bullying social big data. As a result, approximately 2,400 key terms were extracted in top-, middle-, and lower-level categories, concerning domains of participants, causes, types, location, region, and intervention. The study contributes to the literature by explaining the ontology development process and proposing a novel alternative research model that uses social big data in school bullying research. Findings from this ontology study may provide a basis for social big data research. Practical implications of this study lie in not only helping to understand the experience of school bullying participants, but also in offering a macro perspective on school bullying as a social phenomenon.

• Journal of Digital Convergence
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• v.15 no.3
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• pp.17-25
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• 2017

Horizon scanning that one of the methods for future prediction is adaptable way of establishing the policy strategy based on big data. This study aims to understand the social problems scientifically utilized horizon scanning technique, and contribute to public policy formulation based on scanning analysis. In this paper, we proposed a public opinion framework for public policy based on social bigdata, and then confirmed the feasibility this framework by analysis of the relationship between public opinion and results after implementation of public policy. Consequently, based on the analysis, we also drew implications of policy formulation about 'free childcare for under 5-years of age' as an object of study. The method that collects public opinion is very important to effective policy establishment and make contribution to constructing national response systems for social development.