• Title/Summary/Keyword: Cultural Big Data

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Constructing a Knowledge Graph for Improving Quality and Interlinking Basic Information of Cultural and Artistic Institutions (문화예술기관 기본정보의 품질개선과 연계를 위한 지식그래프 구축)

  • Euntaek Seon;Haklae Kim
    • Journal of the Korean Society for information Management
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    • v.40 no.4
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    • pp.329-349
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    • 2023
  • With the rapid development of information and communication technology, the speed of data production has increased rapidly, and this is represented by the concept of big data. Discussions on quality and reliability are also underway for big data whose data scale has rapidly increased in a short period of time. On the other hand, small data is minimal data of excellent quality and means data necessary for a specific problem situation. In the field of culture and arts, data of various types and topics exist, and research using big data technology is being conducted. However, research on whether basic information about culture and arts institutions is accurately provided and utilized is insufficient. The basic information of an institution can be an essential basis used in most big data analysis and becomes a starting point for identifying an institution. This study collected data dealing with the basic information of culture and arts institutions to define common metadata and constructed small data in the form of a knowledge graph linking institutions around common metadata. This can be a way to explore the types and characteristics of culture and arts institutions in an integrated way.

Analysis of COVID-19 Pandemic based on Massive Big Data Analysis (대규모 빅데이터 분석 기반 COVID-19 Pandemic 분석결과)

  • Kim, Na-Hyeon;Oh, Hayoung
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.25 no.4
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    • pp.495-500
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    • 2021
  • This paper is to identify the recent growing crisis from coronavirus infections-19, using domestic news big data. This paper analyzed media articles related to the crisis caused by COVID-19 using the Korea Press Foundation's news big data analysis system 'BIGKinds'. In this paper, a total of 54 media articles were extracted around the keywords 'Corona' and 'Crisis', after a period of about 10 months. We want to understand the correlation coefficient between the two keywords "Corona" and "Crisis" and to understand what kind of crisis the COVID-19 is facing for each representative category of economy, society, international and cultural. As the COVID-19 crisis is taking a heavy toll on the economy, society and any other categories, this research using big data is expected to be used as a basic data to overcome the crisis of COVID-19.

A Study on the Value Factors of Culture Consumers for Corporate Culture Marketing through Big Data Techniques (빅데이터 기법을 통한 기업 문화마케팅을 위한 문화소비자의 가치 요소 연구)

  • Oh, Se Jong
    • The Journal of the Convergence on Culture Technology
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    • v.6 no.1
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    • pp.31-36
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    • 2020
  • Corporate Culture Marketing is a marketing tool that enhances a company's cultural image or conveys its image through culture. Culture Consumer value analysis is important predictive data in identifying the value and pursuit of life in individual consumption behavior, explaining the choice behavior of culture consumers, and serves as the basis for decision making. The research method was linked to the text mining and opinion mining techniques of big data, and extracted positive, negative and neutral words. The analysis targets culture consumers participating in concerts at Hyundai Card's 'Super Concert', which is subject to domestic consumers, and CJ ENM's 'KCON', which is subject to foreign consumers. The culture consumer value elements of corporate culture marketing are the basic conditions, and they were derived as 'Consensus Communication (Expression of Sensibility)', 'Participation Sharing(VIP Belonging)', 'Social Change Issue', 'Differentiating Services', 'Price Discount Benefit' and 'Location Quality'. In the future, we will need to foster 'Culture Technology Marketers' and apply them in areas such as arts management planning, cultural investment, cultural distribution, cultural space, Corporate Culture, CSR and K-pop marketing to enhance corporate interests and brand value and enhance brand value.

A Study on the Planning Guideline of Individual Space Size for Public Library (공공도서관 세부소요공간 규모기준에 관한 연구)

  • Lim, Ho-Kyun;Ko, Hung-Kwon
    • Korean Institute of Interior Design Journal
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    • v.21 no.5
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    • pp.390-398
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    • 2012
  • The purpose of this study was to analyze the planning guideline of individual space size for public library. The 26 cases were selected from the data of outstanding libraries built after the year 2000. The paper focused on the comparison between the data from analysis and the guideline from manual book of public library. The result of this study was as followed ; The first, reference reading rooms were open-plan rather than segmented. The second, the percentages of reference reading spaces from the data were lower than the guidelines. It proved the fact that the role of public library expanded to cultural community space. The third, children's space retained sufficient numbers of book collections. It represented that people realized the importance of children's library in terms of cultural education. The fourth, the percentage of space size of cultural area showed high amount of numbers. It proved the fact that the public library as community center was required various cultural programs. The fifth, the percentages of preservation library were lower than the guideline in case of the big libraries, while the small libraries were higher. The book collections of detached annex libraries should be linked with the central libraries.

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A Study on the Consumer Perception and Keyword Analysis of Meal-kit Using Big Data

  • Jung, Sunmi;Ryu, Gihwan;Lim, Jeongsook;Kim, Heeyoung
    • International Journal of Internet, Broadcasting and Communication
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    • v.14 no.2
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    • pp.206-211
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    • 2022
  • As the level of consumption is improved and cultural life is pursued, the consumer's consciousness structure is rapidly changing, and the demand for product selection level, variety, and quality is becoming more diverse. The restaurant economy is falling due to the prolonged COVID-19, the economic recession, income decline, and changes in population structure and lifestyle, but the Meal- kit market is growing rapidly. This study aims to identify the consumer perception of Meal-kit, which is rapidly growing as an alternative to existing meals in the fields of dining out, food, and distribution due to the development of technology and social environment using big data. As a result of the analysis, the keywords with the highest frequency of appearance were in the order of Meal-kit, Cooking, Product, Launching, and Market and were divided into 8 groups through the CONCOR analysis. We want to identify consumer trends related to the key keywords of Meal-kit, present effective data related to Meal-kit demand for Meal-kit specialized companies, and provide implications for establishing marketing strategies for differentiated competitive advantage.

A Case Study on the Distribution of Cultural Contents in the Untact Era Using Big Data (빅데이터를 활용한 언택트 시대의 1인 콘텐츠 유통 사례 분석)

  • Wang, Deok-won;Kim, Jeong-hyeon;Son, Hye-ji;Jeon, Min-jun;Choi, Hun
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2021.05a
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    • pp.301-302
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    • 2021
  • After the Korona 19, "social distancing" was implemented, existing "pop culture" or entertainment programs were unable to communicate in both directions and declined. Since then, "Untact content" has shown its potential to grow due to untouch performances such as BTS' "Bangbangcon" and the rapid growth of Netflix, a global OTT (online video service). In addition, most of the global and Untact content is online and digital, which means a huge amount of big data will be poured out. Therefore, analyzing the big data poured out during the distribution of untact content will help us identify consumers' needs, and the growth expectations will also be high. Therefore, we would like to explore the research cases that have been conducted in existing studies regarding the subject of the study and analyze how big data can affect the distribution of content in the Untact era.

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A Study on Fashion Startup Ecosystem Trends in Korea Using Big Data Analysis - Focusing on Newspaper Articles in 2012-2022 - (빅데이터 분석을 활용한 우리나라 패션 스타트업 생태계의 추세 연구 - 2012~2022년 신문기사를 중심으로 -)

  • Soojung Lim;Sunjin Hwang
    • Journal of Fashion Business
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    • v.27 no.1
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    • pp.1-15
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    • 2023
  • This study divided articles into two time periods, from 2012 to 2022, with the aim of using big data analysis to look at patterns in the ecosystem of fashion start-ups. The research method extracted top keywords based on TF(Term Frequency) and TF-IDF(Term Frequency-Inverse Document Frequency), analyzed the network, and derived centrality values. As a result of comparing the first and second fashion startup ecosystems, elements of policy, support, market, finance, and human capital were derived in the first period. In addition, in the second period, elements of policy, support, market, finance, and culture were derived. In the first period, the fashion startup ecosystem focused on fostering new designer startups by emphasizing support, finance, and human capital factors and focusing on policies. Meanwhile, in the second period, online-based fashion platform startups and fashion tech startups appeared with the support of digital transformation and fulfillment services triggered by COVID-19(Corona Virus Disease 19), private finances were emphasized, and cultural factors were derived along with success stories of fashion startups. This study is meaningful in that it helps in developing strategies for fashion startups to grow into sustainable companies.

A Study of Slow Fashion on YouTube Through Big Data Analysis (유튜브에 나타난 슬로우 패션의 빅데이터 분석)

  • Sen Bin;Haejung Yum
    • Journal of Fashion Business
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    • v.27 no.4
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    • pp.50-66
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    • 2023
  • The purpose of this study was to examine the word distribution and topic distribution of slow fashion appearing on YouTube in detail and identify the characteristics and aspects related to fashion design through big data analysis and content analysis methods. The specific research results were as follows. First, in the results of the word distribution analysis, "item" appeared the most, 203 times. Also, "one-piece" was a point to pay attention to, as the item had the highest frequency. Second, a total of 5 topics were defined in the topic distribution analysis: topic 1 was "vintage products," topic 2 was "fashion items," topic 3 was "eco-friendly," topic 4 was "life quality emphasis," and topic 5 was "prudent consumption." Third, looking at the relationship between word distribution and topic distribution above, Korean slow fashion on YouTube was actively selecting related design elements that express vintage images in clothing life regardless of trends. In addition, there was a tendency to pursue various basic and high-quality items. Other than those findings, basic items tended to be reinterpreted in various ways through styling methods matched to the vintage image. Lastly, the tendency of slow and small-volume production appeared to emphasize handicrafts and the cultural values of fashion products.

Risk based policy at big data era: Case study of privacy invasion (빅 데이터 시대 위험기반의 정책 - 개인정보침해 사례를 중심으로 -)

  • Moon, Hyejung;Cho, Hyun Suk
    • Informatization Policy
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    • v.19 no.4
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    • pp.63-82
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    • 2012
  • The world's best level of ICT(Information, Communication and Technology) infrastructure has experienced the world's worst level of ICT accident in Korea. The number of major accidents of privacy invasion has been three times larger than the total number of Internet user of Korea. The cause of the severe accident was due to big data environment. As a result, big data environment has become an important policy agenda. This paper has conducted analyzing the accident case of data spill to study policy issues for ICT security from a social science perspective focusing on risk. The results from case analysis are as follows. First, ICT risk can be categorized 'severe, strong, intensive and individual'from the level of both probability and impact. Second, strategy of risk management can be designated 'avoid, transfer, mitigate, accept' by understanding their own culture type of relative group such as 'hierarchy, egalitarianism, fatalism and individualism'. Third, personal data has contained characteristics of big data such like 'volume, velocity, variety' for each risk situation. Therefore, government needs to establish a standing organization responsible for ICT risk policy and management in a new big data era. And the policy for ICT risk management needs to balance in considering 'technology, norms, laws, and market'in big data era.

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Cultural Region-based Clustering of SNS Big Data and Users Preferences Analysis (문화권 클러스터링 기반 SNS 빅데이터 및 사용자 선호도 분석)

  • Rho, Seungmin
    • Journal of Advanced Navigation Technology
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    • v.22 no.6
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    • pp.670-674
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    • 2018
  • Social network service (SNS) related data including comments/text, images, videos, blogs, and user experiences contain a wealth of information which can be used to build recommendation systems for various clients' and provide insightful data/results to business analysts. Multimedia data, especially visual data like image and videos are the richest source of SNS data which can reflect particular region, and cultures values/interests, form a gigantic portion of the overall data. Mining such huge amounts of data for extracting actionable intelligence require efficient and smart data analysis methods. The purpose of this paper is to focus on this particular modality for devising ways to model, index, and retrieve data as and when desired.