• International Journal of Internet, Broadcasting and Communication
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• 제15권3호
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• pp.1-7
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• 2023

Since the first outbreak of COVID-19 in 2019, it has caused a huge blow to the restaurant industry. However, as social distancing was lifted as of April 2022, the restaurant industry gradually recovered, and as a result, interest in restaurant start-ups increased. Therefore, in this paper, big data analysis was conducted by selecting "restaurant start-up" as a key keyword through social media big data analysis using Textom and then conducting word frequency and CONCOR analysis. The collection period of keywords was selected from May 1, 2022 to May 23, 2023, after the lifting of social distancing due to COVID-19, and based on the analysis, the development of a restaurant start-up consulting chatbot service is proposed.

• 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.

• 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.

• 한국체육학회지인문사회과학편
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• 제56권4호
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• pp.397-413
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• 2017

본 연구의 목적은 4차 산업혁명의 스포츠 현장 적용을 위한 탐색적 연구를 통하여 스포츠 업계 종사자들이 소셜 빅데이터를 직접 다루고 활용하기 위한 사례를 소개하고, 관련 정보를 제공하는 것이다. 수집된 문헌은 국내 외 학술 DB로부터 '소셜 빅데이터', '스포츠'와 관련된 문헌 302편이며, 분석된 문헌은 86편(국내 28편, 국외 58편)이다. 연구 결과, 스포츠산업 분야에 적용 가능한 소셜 빅데이터 분석 연구는 1) 스포츠 팬들의 관심사 및 스포츠 이벤트에 대한 주요 이슈 분석, 2) 미디어스포츠 인게이지먼트 연구, 3) 사용자 감성을 이용한 경기 승패 예측, 4) 프로선수 연봉 산정 모델 개발, 5) 연구동향 분석 등이 될 수 있다. 결론적으로, 스포츠산업 경영 분야에서 소셜 빅데이터 분석 기술은 다양하게 활용될 수 있기 때문에, 스포츠 업계 종사자들이 소셜 빅데이터 분석 기술을 직접 다루고 이를 활용하기 위해서는 IT기술에 대한 선행 학습, 연구수행을 통한 노하우 습득, 그리고 융합적인 사고의 전환이 필요하다.

• 한국BIM학회 논문집
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• 제13권4호
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• pp.106-114
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• 2023

In this study, we developed a method to quantify urban social costs using mobile sensing data, providing a novel approach to urban planning. By collecting and analyzing extensive mobile data over time, we transformed travel patterns into measurable social costs. Our findings highlight the effectiveness of big data in urban planning, revealing key correlations between transportation modes and their associated social costs. This research not only advances the use of mobile data in urban planning but also suggests new directions for future studies to enhance data collection and analysis methods.

• 한국컴퓨터정보학회논문지
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• 제26권1호
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• pp.163-170
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• 2021

빅데이터가 여러 분야에서 다양하게 접목됨에 따라 빅데이터 시장이 하드웨어로부터 시작해서 서비스 소프트웨어 부문으로 확장되고 있다. 특히 빅데이터 의미 파악 및 이해 능력, 분석 결과 등 총체적이고 직관적인 시각화를 위하여 애플리케이션을 제공하는 거대 플랫폼 시장으로 확대되고 있다. 그 중에서 SNS(Social Network Service) 등과 같은 소셜 미디어를 활용한 빅데이터 추출 및 분석에 대한 수요가 기업 뿐만 아니라 개인에 이르기까지 매우 활발히 진행되고 있다. 그러나 이처럼 사용자 트렌드 분석과 마케팅을 위한 소셜 미디어 데이터의 수집 및 분석에 대한 많은 수요에도 불구하고, 다양한 소셜 미디어 서비스 인터페이스의 이질성으로 인한 동적 연동의 어려움과 소프트웨어 플랫폼 구축 및 운영의 복잡성을 해결하기 위한 연구가 미흡한 상태이다. 따라서 본 논문에서는 소셜 미디어 데이터의 수집에서 추출 및 분류에 이르는 과정을 하나로 통합하여 운영할 수 있는 프레임워크를 개발하는 방법에 대해 제시한다. 제시된 프레임워크는 이질적인 소셜 미디어 데이터 수집 채널의 문제를 어댑터 패턴을 통해 해결하고, 의미 연관성 기반 추출 기법과 주제 연관성 기반 분류 기법을 통해 소셜 토픽 추출과 분류의 정확성을 높였다.

• 한국의류산업학회지
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• 제18권1호
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• pp.48-62
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• 2016

Consumers have come to demand high quality, affordable prices, and innovative product designs of the outdoor wear market due to their well-being and leisure oriented lifestyle. A new system of business in outdoor wear has emerged in the process through which corporations have endeavored to satisfy such consumer needs. Outdoor wear brands have utilized social network services (SNS) such as Facebook and Twitter as means of marketing and have built close relations with consumers based on communication through these media. Recently, explosively escalating SNS data are referred to as social big data, and now that every consumer online is a commentator, reviewer, and publisher, the outdoor wear market and all of its brands have to stop talking and start listening to how they are perceived. Therefore, this study employs Social $Metrics^{TM}$, a social big data analysis solution by Daumsoft, Inc., to verify changes in the allusions related to outdoor wear market found on SNS. This study aims to identify changes in consumer perceptions of outdoor wear based on changes in outdoor wear search words and trends in positive and negative public opinion found in SNS social big data. In addition, products of interest, the major brands mentioned, the attributes taken into consideration during purchases of products, and consumers' psychology were categorized and analyzed by means of keywords related to outdoor wear brands found on SNS. The results of this study will provide fundamental resources for outdoor wear brands' market entry and brand strategy implementation in the future.

• 수산해양교육연구
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• 제29권2호
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• pp.593-606
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• 2017

This study aims to provide preliminary data capable of suggesting directivity of an initiating start by understanding consumer awareness through analysis of SNS social big data on marine sports. This study selected windsurfing, yacht, jet ski, scuba diving and sea fishing as research subjects, and produced following results by setting period of total 1 month from January 22 through February 22, 2017 on the SNS (twitter, blog) through the Social MatrixTM service of Daumsoft Co., Ltd., and analyzing frequency of mention, associated words etc. First, sports that was mentioned the most out of marine sports was yacht, which was 3,273 cases on twitter and 2,199 on blog respectively. Second, the word which was shown the most associated with marine sports was the attribute showing unique characteristic of marine sports, which was 6,261 cases in total.

• International journal of advanced smart convergence
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• 제12권1호
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• pp.164-172
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• 2023

In this study, we identify the recognition of 'The First Slam Dunk', which is gaining popularity as a sports-based cartoon through big data analysis of social media channels, and provide basic data for the development and development of various contents in the sports industry. Social media channels collected detailed social big data from news provided on Naver and Google sites. Data were collected from January 1, 2023 to February 15, 2023, referring to the release date of 'The First Slam Dunk' in Korea. The collected data were 2,106 Naver news data, and 1,019 Google news data were collected. TF and TF-IDF were analyzed through text mining for these data. Through this, semantic network analysis was conducted for 60 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 the study, the keyword with the high frequency in relation to the subject in consideration of TF and TF-IDF appeared 4,079 times as 'The First Slam Dunk' was the keyword with the high frequency among the frequent keywords. Next are 'Slam Dunk', 'Movie', 'Premiere', 'Animation', 'Audience', and 'Box-Office'. Based on these results, 60 high-frequency appearing keywords were extracted. After that, semantic metrics and centrality analysis were conducted. Finally, a total of 6 clusters(competing movie, cartoon, passion, premiere, attention, Box-Office) were formed through CONCOR analysis. Based on this analysis of the semantic network of 'The First Slam Dunk', basic data on the development plan of sports content were provided.

• International Journal of Advanced Culture Technology
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• 제11권4호
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• pp.279-285
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• 2023

This study provides academic implications by considering trends of domestic research regarding therapy for Mental disorder schizophrenia and psychosocial. For the analysis of this study, text mining with the use of R program and social network analysis method have been used and 65 papers have been collected The result of this study is as follows. First, collected data were visualized through analysis of keywords by using word cloud method. Second, keywords such as intervention, schizophrenia, research, patients, program, effect, society, mind, ability, function were recorded with highest frequency resulted from keyword frequency analysis. Third, LDA (latent Dirichlet allocation) topic modeling result showed that classified into 3 keywords: patient, subjects, intervention of psychosocial, efficacy of interventions. Fourth, the social network analysis results derived connectivity, closeness centrality, betweennes centrality. In conclusion, this study presents significant results as it provided basic rehabilitation data for schizophrenia and psychosocial therapy through new research methods by analyzing with big data method by proposing the results through visualization from seeking research trends of schizophrenia and psychosocial therapy through text mining and social network analysis.