• Title/Summary/Keyword: 텍스트 연구

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The Diffusion of Internet of Things: Forecasting Technologies and Company Strategies using Qualitative and Quantitative Approach (사물인터넷의 확산: 정성적·정량적 기법을 이용한 기술 및 기업 전략 예측)

  • Lee, Saerom;Jahng, Jungjoo
    • The Journal of Society for e-Business Studies
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    • v.20 no.4
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    • pp.19-39
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    • 2015
  • Internet of Things (IoT) is expected to provide efficiency and convenience in human life by integrating the Internet into the things that we use in daily lives. IoT can not only create new businesses but also can bring great changes in our lives thanks to the various ways of technical application: defining relationships among things or automatic use of technology by analyzing the usage pattern. This study uses the qualitative research of interviewing the experts to predict the changes that IoT technology is expected to bring in our lives. In addition, this paper analyzes news articles about internet of things in Korea using text-network analysis. This study also discusses the factors which need to be considered to put IoT into successful use in business contexts.

Categorizing Sub-Categories of Mobile Application Services using Network Analysis: A Case of Healthcare Applications (네트워크 분석을 이용한 애플리케이션 서비스 하위 카테고리 분류: 헬스케어 어플리케이션 중심으로)

  • Ha, Sohee;Geum, Youngjung
    • The Journal of Society for e-Business Studies
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    • v.25 no.3
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    • pp.15-40
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    • 2020
  • Due to the explosive growth of mobile application services, categorizing mobile application services is in need in practice from both customers' and developers' perspectives. Despite the fact, however, there have been limited studies regarding systematic categorization of mobile application services. In response, this study proposed a method for categorizing mobile application services, and suggested a service taxonomy based on the network clustering results. Total of 1,607 mobile healthcare services are collected through the Google Play store. The network analysis is conducted based on the similarity of descriptions in each application service. Modularity detection analysis is conducted to detects communities in the network, and service taxonomy is derived based on each cluster. This study is expected to provide a systematic approach to the service categorization, which is helpful to both customers who want to navigate mobile application service in a systematic manner and developers who desire to analyze the trend of mobile application services.

A Study on the Relationship between Class Similarity and the Performance of Hierarchical Classification Method in a Text Document Classification Problem (텍스트 문서 분류에서 범주간 유사도와 계층적 분류 방법의 성과 관계 연구)

  • Jang, Soojung;Min, Daiki
    • The Journal of Society for e-Business Studies
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    • v.25 no.3
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    • pp.77-93
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    • 2020
  • The literature has reported that hierarchical classification methods generally outperform the flat classification methods for a multi-class document classification problem. Unlike the literature that has constructed a class hierarchy, this paper evaluates the performance of hierarchical and flat classification methods under a situation where the class hierarchy is predefined. We conducted numerical evaluations for two data sets; research papers on climate change adaptation technologies in water sector and 20NewsGroup open data set. The evaluation results show that the hierarchical classification method outperforms the flat classification methods under a certain condition, which differs from the literature. The performance of hierarchical classification method over flat classification method depends on class similarities at levels in the class structure. More importantly, the hierarchical classification method works better when the upper level similarity is less that the lower level similarity.

Mass Media and Social Media Agenda Analysis Using Text Mining : focused on '5-day Rotation Mask Distribution System' (텍스트 마이닝을 활용한 매스 미디어와 소셜 미디어 의제 분석 : '마스크 5부제'를 중심으로)

  • Lee, Sae-Mi;Ryu, Seung-Eui;Ahn, Soonjae
    • The Journal of the Korea Contents Association
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    • v.20 no.6
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    • pp.460-469
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    • 2020
  • This study analyzes online news articles and cafe articles on the '5-day Rotation Mask Distribution System', which is emerging as a recent issue due to the COVID-19 incident, to identify the mass media and social media agendas containing media and public reactions. This study figured out the difference between mass media and social media. For analysis, we collected 2,096 full text articles from Naver and 1,840 posts from Naver Cafe, and conducted word frequency analysis, word cloud, and LDA topic modeling analysis through data preprocessing and refinement. As a result of analysis, social media showed real-life topics such as 'family members' purchase', 'the postponement of school opening', ' mask usage', and 'mask purchase', reflecting the characteristics of personal media. Social media was found to play a role of exchanging personal opinions, emotions, and information rather than delivering information. With the application of the research method applied to this study, social issues can be publicized through various media analysis and used as a reference in the process of establishing a policy agenda that evolves into a government agenda.

The Analysis on the KAIE Articles using Social Network Analysis (사회연결망 분석을 활용한 정보교육학회 논문 분석)

  • Park, SunJu
    • Journal of The Korean Association of Information Education
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    • v.20 no.6
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    • pp.543-552
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    • 2016
  • Recently, a number of researches focus on social network analysis and it is applied to various fields not only in social science area but also in natural science area. Therefore, the social network analysis and the text analysis were conducted in order to analyze the current trend of the theses in information education field. The result indicated that the most frequently mentioned words were consistent with the development of information technology and the change in information education curriculum. That is, the mentioned words were computer aided instruction (CAI) and courseware for period 1, ICT for period 2, smart and scratch for period 3, and in period 4, computational thinking ability and coding appeared for the first time. Moreover, as the result of social network analysis, it concluded the research topics became more complicated and detailed as the words diversified throughout the period in which the simplified network in period 1 changed its configuration into a structure with more diversified words of higher centrality.

A Study on the Policy Convergence of Forest Policy : A Paradigm Sift to Convergence between Forest Development and Preservation (산림정책융합에 관한 연구 : 산림이용·개발 및 보전의 융합패러다임으로의 변화)

  • Chang, Je-Won;Park, Yong-Sung
    • Journal of Digital Convergence
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    • v.13 no.6
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    • pp.13-28
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    • 2015
  • In accordance with importance of the economic value of forests and forest use, the paradigm of development and use has emerged as the dominant paradigm of forest policy. As forests are recognized as an important means of Wellness, the government pursues a policy convergence between forest use and conservation. So, this article analyzed whether the change of forestry convergence paradigm is reflected in policy or not. The purpose of this study was to analyze through content analysis and network analysis, whether the new combined text value are fused in how forest policy. According to the results, the function of utilization which is off the traditional forestry industry and recreation, wellness are acquired a greater importance in the 5th plan than 4th plan. But the 5th plan is insufficient to establish of foundation for forestry management and welfare functions. The evidence suggest a sign of sustained paradigm convergency in forest policy of Korea. As the policy implication in establishing national forest master plan, it is necessary to strengthen policy capability to pursue sustainable forestry utilization, which can converge forest use and conservation.

Analysis Study on Trends of Library Development Plan by Using Big Data Analysis (빅데이터 분석 기법을 활용한 도서관발전종합계획 동향 분석 연구)

  • Kim, Dongseok;Noh, Younghee
    • Journal of the Korean BIBLIA Society for library and Information Science
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    • v.29 no.2
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    • pp.85-108
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    • 2018
  • This study aimed to analyze media reports of the Comprehensive Library Advancement Plan using big data analysis in order to determine trends and implications by period. To do so, related data from 2009 to 2017 were collected from major domestic web portal sites. Words in the collected data were refined through the text mining process and frequency, centrality, and structural equivalence analyses were performed. Results confirmed that, during the implementation of the first and the second phases of the Comprehensive Library Advancement Plan, the focus of the library policy changed from external growth to strengthening internal stability and advancement of library operation, and the media coverage were limited to specific policies such as expansion of library facilities. Findings from this study will serve as useful material for ascertaining the approach to perceive and understand the national library policy represented by the Comprehensive Library Advancement Plan.

A Study on the Effect of Presentation Modes of Health Information on Information Perception (건강정보 제시유형이 정보의 인지에 미치는 영향에 관한 연구)

  • Nam, Jae Woo;Kim, Seonghee
    • Journal of the Korean BIBLIA Society for library and Information Science
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    • v.24 no.4
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    • pp.217-238
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    • 2013
  • We investigated how combining different types of images with written text affects the comprehension of health related information. The types of images were picture, photograph, and X-ray. 47 four year college students were recruited for the experiment. The independent variables in this study included information presentation format, vividness of image, and the degree of awareness for the disease. The dependent variables were recognition and recall for information. The results showed that the information with images in recognition and recall had higher score than information with written text only. In regard to the effect of different kinds of images on comprehension of health information, information with picture had higher score than the information with photograph and X-ray. The vividness of image were found to work as a negative factor on the recognition of information. Finally, the degree of awareness of disease also failed to have any significant effect on subjects' recall and recognition. This research has implications for the contents design of health related website.

A Comparative Analysis of the Prediction Models for the Direction of Stock Price Using the Online Company Reviews (기업 리뷰 정보를 활용한 주가 방향 예측 모델 비교 분석)

  • Lim, Yongtaek;Lim, Heuiseok
    • Journal of the Korea Convergence Society
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    • v.11 no.8
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    • pp.165-171
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    • 2020
  • Most of the stock price prediction research using text mining uses news and SNS data. However, there is a weakness that it is difficult to get honest and vivid information about companies from them. This paper deals with the problem of the prediction for the direction of stock price by doing text mining the online company reviews of internal staff indicating employee satisfaction. The comparative analysis of the prediction models for the direction of stock price showed the prediction model, which adds internal employee reviews, has better performance than those that did not. This paper presents the convergence study using natural language processing in financial engineering. In the field of stock price prediction, This paper pursued a new methodology that used employee satisfaction. In practice, it is expected to provide useful information in the field of forecasting stock price direction.

Crisis Prediction of Regional Industry Ecosystem based on Text Sentiment Analysis Using News Data - Focused on the Automobile Industry in Gwangju - (뉴스 데이터를 활용한 텍스트 감성분석에 따른 지역 산업생태계 위기 예측 - 광주 지역 자동차 산업을 중심으로 -)

  • Kim, Hyun-Ji;Kim, Sung-Jin;Kim, Han-Gook
    • The Journal of the Korea Contents Association
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    • v.20 no.8
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    • pp.1-9
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    • 2020
  • As the aging problem of the regional industry ecosystem has gradually become serious, research to measure and regenerate the regional industry ecosystem decline has been actively conducted. However, little research has been done on regional industry ecosystem crises. Crisis emerges radically over a short period of time, and it is often impossible to respond by post-response, so you must respond before the crisis occurs. In other words, it is more necessary and required when looking at the crisis early and taking a proactive response from a long-term perspective. Therefore, it is necessary to develop a predictive model that can proactively recognize and respond to the crisis in the regional industry ecosystem. Therefore, this study checked the possibility of predicting the risk of regional industry and market according to the emotional score of the news by using large-scale news data. News sentiment analysis was performed using the Google sentiment analysis API, and this was organized by month to check the correlation between actual events.