• Title/Summary/Keyword: keyword networks

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Smart SNS Map: Location-based Social Network Service Data Mapping and Visualization System (스마트 SNS 맵: 위치 정보를 기반으로 한 스마트 소셜 네트워크 서비스 데이터 맵핑 및 시각화 시스템)

  • Yoon, Jangho;Lee, Seunghun;Kim, Hyun-chul
    • Journal of Korea Multimedia Society
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    • v.19 no.2
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    • pp.428-435
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    • 2016
  • Hundreds of millions of new posts and information are being uploaded and propagated everyday on Online Social Networks(OSN) like Twitter, Facebook, or Instagram. This paper proposes and implements a GPS-location based SNS data mapping, analysis, and visualization system, called Smart SNS Map, which collects SNS data from Twitter and Instagram using hundreds of PlanetLab nodes distributed across the globe. Like no other previous systems, our system uniquely supports a variety of functions, including GPS-location based mapping of collected tweets and Instagram photos, keyword-based tweet or photo searching, real-time heat-map visualization of tweets and instagram photos, sentiment analysis, word cloud visualization, etc. Overall, a system like this, admittedly still in a prototype phase though, is expected to serve a role as a sort of social weather station sooner or later, which will help people understand what are happening around the SNS users, systems, society, and how they feel about them, as well as how they change over time and/or space.

A Study on the Change of Tourism Marketing Trends through Big Data

  • Se-won Jeon;Gi-Hwan Ryu
    • International journal of advanced smart convergence
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    • v.13 no.2
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    • pp.166-171
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    • 2024
  • Recently, there has been an increasing trend in the role of social media in tourism marketing. We analyze changes in tourism marketing trends using tourism marketing keywords through social media networks. The aim is to understand marketing trends based on the analyzed data and effectively create, maintain, and manage customers, as well as efficiently supply tourism products. Data was collected using web data from platforms such as Naver, Google, and Daum through TexTom. The data collection period was set for one year, from December 1, 2022, to December 1, 2023. The collected data, after undergoing refinement, was analyzed as keyword networks based on frequency analysis results. Network visualization and CONCOR analysis were conducted using the Ucinet program. The top words in frequency were 'tourists,' 'promotion,' 'travel,' and 'research.' Clusters were categorized into four: tourism field, tourism products, marketing, and motivation for visits. Through this, it was confirmed that tourism marketing is being conducted in various tourism sectors such as MICE, medical tourism, and conventions. Utilizing digital marketing via online platforms, tourism products are promoted to tourists, and unique tourism products are developed to increase city branding and tourism demand through integrated tourism content. We identify trends in tourism marketing, providing tourists with a positive image and contributing to the activation of local tourism.

선박사고 기인 해양재난 피해축소를 위한 해양과학기술 개발수요 도출

  • Jang, Deok-Hui;Gang, Gil-Mo
    • Proceedings of the Korea Technology Innovation Society Conference
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    • 2015.05a
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    • pp.508-525
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    • 2015
  • The purpose of this study is to derive the demands to develop marine science technology to reduce damage of disasters caused by boating accidents. This study analyzed the press release to identify the factors of damages that can result from boating accidents and derive the demands for technology development to approach from the perspective of marine science technology to avoid the elements of damage. For this purpose, this study analyzed the contents of about 77,000 articles posted for a month after the tragedy of the Sewol (April 16 - May 15) to derive the keywords and used SNA for the network analysis of each keyword. The findings of the analysis showed that there were five networks and each network consisted of different aspects of technology development to prepare for the marine disasters. Based on these findings, this study derived the demands for technology development from the perspective of marine science technology required to prepare for the possible marine disasters caused by vessels in the future.

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Demands to Develop Marine Science Technology to Reduce Damage of Disasters Caused by Marine Accidents (선박기인 해양재난 피해축소를 위한 해양과학기술 개발수요 도출)

  • Jang, Duckhee;Kang, Gil-Mo;Kim, Jin-Young
    • Ocean and Polar Research
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    • v.37 no.4
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    • pp.369-383
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    • 2015
  • The purpose of this study is to ascertain the demands for developing marine science technology to reduce fatalities caused by marine accidents. For this purpose, we analyzed the contents of about 77,000 news articles posted for a month after the tragedy of the Sewol (April 16~May 15) to identify keywords and then we used the Social Network Analysis (SNA) for each keyword. The findings of the analysis show that there are five networks and that each one reveals different aspects about technology development to prepare for marine accidents. Based on these findings, we categorized three kinds of demands for technology development from the perspective of marine science technology: provision of the information about the marine environment, development of equipment and technology to overcome extreme environments, and the establishment of a field support system.

Exploratory Analysis of Platform Government Research (플랫폼 정부 연구의 탐색적 분석)

  • Shin, Sun-Young;Suh, Chang-Kyo
    • The Journal of Information Systems
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    • v.29 no.1
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    • pp.159-179
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    • 2020
  • Purpose: We present a scientometric review of the literature on platform government to serve three primary purposes: First, to cluster researches on platform government based on the research issues; second, to identify the major papers, authors, and keywords in the domain; and third, to explore the promising research areas of platform government. Design/methodology/approach: We collected the platform government research from Web of Science, and analyzed 1,536 articles that was published during time span of 1998-2019. Next, co-citation networks are constructed and analyzed by using CiteSpace to visualize the domain clusters and dynamic research trends in the platform government domain. Findings: We identified 13 sub areas of the platform government research: global investigation, consumer product quality, digital agora, civic crowd funding, and open data use etc. We also visualize the top 20 references with the strongest citation bursts, co-authors network, co-occurring keyword network, and timeline of co-citation clusters.

Implementation of Extracting Specific Information by Sniffing Voice Packet in VoIP

  • Lee, Dong-Geon;Choi, WoongChul
    • International journal of advanced smart convergence
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    • v.9 no.4
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    • pp.209-214
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    • 2020
  • VoIP technology has been widely used for exchanging voice or image data through IP networks. VoIP technology, often called Internet Telephony, sends and receives voice data over the RTP protocol during the session. However, there is an exposition risk in the voice data in VoIP using the RTP protocol, where the RTP protocol does not have a specification for encryption of the original data. We implement programs that can extract meaningful information from the user's dialogue. The meaningful information means the information that the program user wants to obtain. In order to do that, our implementation has two parts. One is the client part, which inputs the keyword of the information that the user wants to obtain, and the other is the server part, which sniffs and performs the speech recognition process. We use the Google Speech API from Google Cloud, which uses machine learning in the speech recognition process. Finally, we discuss the usability and the limitations of the implementation with the example.

A Study on the Intellectual Structure Networks of International Collaboration in Psychiatry (정신의학 분야 국제공동연구의 지적구조 네트워크 분석)

  • Kim, Eunju;Roh, Sungwon;Nam, Taewoo
    • Journal of the Korean Society for information Management
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    • v.33 no.1
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    • pp.53-84
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    • 2016
  • This study clarified the intellectual structure of international collaboration in psychiatry based on analyzing networks in order to vitalize for international collaboration in psychiatry in South Korea. The data set was collected from Web of Science citation database during the period from 2009 to 2013. SU="psychiatry" search formulary (means field of psychiatric medical research) was used through advanced retrieval function and a total of 18,590 articles were selected among international collaborations. A total of 85 different keywords were selected from the 18,590 articles, and the results of analysis were as follows. First, this study examined 8 sub-subject areas focusing on disorders, and found that major subject areas could be divided into a total of 8 sub-subject areas. Second, this study examined 6 keywords that have a strong impact, and extend subject areas by promoting intermediation between other keywords Third, this study examined sub-subject areas by using the Knowledge Classification Scheme of the National Research Foundation of Korea through community analysis, and found a total of 15 clusters and a total of 12 sub-subject areas.

A Content Analysis of Journal Articles Using the Language Network Analysis Methods (언어 네트워크 분석 방법을 활용한 학술논문의 내용분석)

  • Lee, Soo-Sang
    • Journal of the Korean Society for information Management
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    • v.31 no.4
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    • pp.49-68
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    • 2014
  • The purpose of this study is to perform content analysis of research articles using the language network analysis method in Korea and catch the basic point of the language network analysis method. Six analytical categories are used for content analysis: types of language text, methods of keyword selection, methods of forming co-occurrence relation, methods of constructing network, network analytic tools and indexes. From the results of content analysis, this study found out various features as follows. The major types of language text are research articles and interview texts. The keywords were selected from words which are extracted from text content. To form co-occurrence relation between keywords, there use the co-occurrence count. The constructed networks are multiple-type networks rather than single-type ones. The network analytic tools such as NetMiner, UCINET/NetDraw, NodeXL, Pajek are used. The major analytic indexes are including density, centralities, sub-networks, etc. These features can be used to form the basis of the language network analysis method.

A Study on Recent Research Trend in New Product Development Using Keyword Network Analysis (키워드 네트워크 분석을 이용한 NPD 연구의 진화 및 연구동향)

  • Pyun, JeBum;Jeong, EuiBeom
    • Journal of Korea Society of Industrial Information Systems
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    • v.23 no.5
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    • pp.119-134
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    • 2018
  • Today, many firms face the environment of high uncertainty and severe competition due to the rapid technology development and the diverse needs of customers. In the business environment, one of the most important ways to gain sustainable competitive advantage and future growth engine is related to NPD (New Product Development), which is a very important issue for practice and academia. Thus, this study intends to provide new values to practitioners and researchers related to NPD by analyzing current research trends and future trends in NPD field. For this, we bibliometrically analyzed keyword networks which consist of keywords that were already published in the eminent journals from Scopus database to generate insights that have not been captured in the previous reviews on the topic. As a result, we could understand the extant research streams in NPD field, and suggest the changes of specific research topics based on the connected relationships among keywords over the time. In addition, we also foresaw the general future research trends in NPD field based on the keywords according to preferential attachment processes. Through this study, it was confirmed that NPD keyword network is a small world network that follows the distribution of power law and the growth of network is formed by link formation by keyword preferential attachment. In addition, through component analysis and centrality analysis, keywords such as Innovation, New product innovation, Risk management, Concurrent engineering, Research and development, and Product life cycle management are highly centralized in NPD keyword network. On the other hand, as a result of examining the change of preferential attachment of keywords over the time, we suggested the required new research direction including i) NPD collaboration with suppliers, ii) NPD considering market uncertainty, iii) NPD considering convergence with the other academic areas like technology management and knowledge management, iv) NPD from SME(Small and medium enterprises) perspective. The results of this study can be used to determine the research trends of NPD and the new research themes for interdisciplinary studies with other disciplines.

A Study on the Research Trend of Elementary Environmental Education through an Analysis of the Network of Author Keywords (저자 키워드 네트워크 분석을 통한 초등 환경교육의 연구 동향 탐색)

  • Kim, Dong-Ryeul
    • Journal of Korean Elementary Science Education
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    • v.36 no.2
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    • pp.113-128
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    • 2017
  • This study aims to investigate the research trend of elementary environmental education. Thus, author keywords were extracted from a total of 197 academic these related to elementary environmental education during two different periods when detailed goals were applied to the 2007 and 2009 revised curriculums respectively, and then this study analyzed the network of author keywords. The results of this study can be summarized as below. Firstly, as a result of analyzing the frequency of author keywords from academic theses related to elementary environmental education, this study discovered 369 author keywords from the period when detailed goals were applied to 2009 revised curriculum. Out of them, it was found that the keyword, 'climate change education', showed the highest frequency, followed by 'environmental literacy' and 'environmental perception', except such central keywords as 'environmental education' and 'elementary school student'. From the period when detailed goals were applied to the 2007 revised curriculum, a total of 394 author keywords were discovered, and the keyword, 'environmental literacy', showed the highest frequency, followed by 'environmental perception' and 'ESD (education for sustainable development)'. Secondly, as a result of analyzing the network of author keywords, this study found out that in the total number of network connections, average connection degree, density and clique, the period when detailed goals were applied to the 2007 revised curriculum was somewhat higher than the period when detailed goals were applied to the 2009 revised curriculum. As a result of analyzing the centrality of author keywords, this study found out that during both the periods, 'environmental perception' and 'environmental literacy' were high in degree centrality and betweenness centrality, except such central keywords as 'environmental education' and 'elementary school student'. As a result of analyzing the components of author keywords as sub-networks, this study discovered 9 components from the period when detailed goals were applied to the 2009 revised curriculum and 6 components from the period when detailed goals were applied to the 2007 revised curriculum. During both the periods, the largest component was composed of keywords high in degree centrality and betweenness centrality.