• 제목/요약/키워드: Public Data Analysis

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Sentiment Analysis on Indonesia Economic Growth using Deep Learning Neural Network Method

  • KRISMAWATI, Dewi;MARIEL, Wahyu Calvin Frans;ARSYI, Farhan Anshari;PRAMANA, Setia
    • 산경연구논집
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    • 제13권6호
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    • pp.9-18
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    • 2022
  • Purpose: The government around the world is still highlighting the effect of the new variant of Covid-19. The government continues to make efforts to restore the economy through several programs, one of them is National Economic Recovery. This program is expected to increase public and investor confidence in handling Covid-19. This study aims to capture public sentiment on the economic growth rate in Indonesia, especially during the third wave of the omicron variant of the covid-19 virus, that is at the time in the fourth quarter of 2021. Research design, data, and methodology: The approach used in this research is to collect crowdsourcing data from twitter, in the range of 1st to 10th October 2021. The analysis is done by building model using Deep Learning Neural Network method. Results: The result of the sentiment analysis is that most of the tweets have a neutral sentiment on the Economic Growth discussion. Several central figures who discussed were Minister of Coordinating for the Economy of Indonesia, Minister of State-Owned Enterprises. Conclusions: Data from social media can be used by the government to capture public responses, especially public sentiment regarding economic growth. This can be used by policy makers, for example entrepreneurs to anticipate economic movements under certain conditions.

Incidence of Online Public Opinion on Guangzhou Simultaneous Renting and Purchasing Policy - A data mining application

  • Wang, Yancheng;Li, Haixian
    • Asian Journal for Public Opinion Research
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    • 제5권4호
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    • pp.266-284
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    • 2018
  • This paper adopts the big data research method, and draws 491 data from the Tianya Forum about the Simultaneous Renting and Purchasing policy of Guangzhou. The qualitative analysis software Nvivo11 is used to cluster the main questions about the Simultaneous Renting and Purchasing policy in the forum. The 36 high-frequency word frequencies are obtained through text clustering. Through rooted theory analysis, the main driving factors for summarizing people's doubts are 9 main categories, 3 core categories, and the model of driving factors for online forums is established. The study finds that resource factors are the most key factor, economic factors are the important drivers, and policy guiding factors are sub-important drivers.

The Role of Public Food Delivery Mobile Applications in the Food Delivery Market: A Game Theory Model

  • Bo-Hun SEO;Da-Hye SONG;Jong Woo CHOI
    • 유통과학연구
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    • 제22권4호
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    • pp.91-104
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    • 2024
  • Purpose: The study aims to assess the current status of domestic public food delivery apps and analyze the process through which sellers choose between private delivery apps and public delivery apps. This involves exploring strategiesto achieve the original purpose of public food delivery apps, which is to enhance the small business owners income and promote consumer welfare by preventing the monopoly of private food delivery apps. Research design, data and methodology: the research methodology is based on a model that introduces adjustments for non-economic effects, considering the preferences of multi-homing consumers, to more realistically reflect the benefits of sellers' choices. For data analysis, real business performance data from 'Daeguro', 'Meokkaebi', and 'Somunnan Shop' were used. Results: The study revealed that if the market share of public delivery apps within a specific region increases beyond a certain level, the benefits for small-business sellers also increase. This leads to the strategic advantage of simultaneously using both delivery apps. Furthermore, the results exhibit a tendency similar to real social phenomena. Conclusions: This analysis confirmed the role of public food delivery apps in the domestic delivery app market and presents policy recommendations, including application integration and the implementation of exclusive public interest functions, to effectively fulfill this role.

기록으로의 공공데이터 관리를 위한 제도적 고찰 - 『공공데이터의 제공 및 이용 활성화에 관한 법률』 분석을 중심으로 - (A Study on Legal Issues of Public Data Management as Records: Focused on Analysis of the Act on Provision and Use of Public Data)

  • 김유승
    • 한국기록관리학회지
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    • 제14권1호
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    • pp.53-73
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    • 2014
  • 본 연구는 "공공데이터법"을 중심으로 관련 법제도를 분석하고, 이를 바탕으로 기록으로서의 공공데이터 관리를 위한 법제도적 미비점을 비판적으로 논하는 데 목적을 둔다. 이를 위해 다학제 영역의 선행연구를 분석하고, 관련 법령에서 사용되고 있는 공공데이터와 그 유사 용어를 이론적 측면에서 논하였으며, 관련 법령의 연혁을 살펴보았다. "공공데이터법"의 제정 의의와 주요내용을 법이 규정한 관련 위원회 및 기관을 중심으로 정리하고, '제공대상 범위설정의 문제', '공공데이터제공책임관의 전문성 및 기능의 실효성', '공공데이터의 낮은 품질', '절차법적 한계와 기록관리 관점의 부재' 등 4가지 논점의 비판적 분석을 통해 법령을 고찰하였다.

정보공개 환경에서 개인정보 보호와 노출 위험의 측정에 대한 통계적 방법 (Review on statistical methods for protecting privacy and measuring risk of disclosure when releasing information for public use)

  • 이용희
    • Journal of the Korean Data and Information Science Society
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    • 제24권5호
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    • pp.1029-1041
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    • 2013
  • 최근 빅데이터의 등장과 정보 공개에 대한 급격한 수요 증가에 따라 자료를 일반에게 공개할 때 개인 정보를 보호해야 하는 필요성이 어느 때보다 절실하다. 본 논문에서는 마이크로 자료와 통계분석 서버를 중심으로 현재까지 제시된 개인정보 노출제한를 위한 통계적 방법, 정보 노출의 개념, 노출 위험을 측정하는 기준들을 개괄적으로 소개한다.

DEA-AR/AHP 결합모형을 이용한 지방의료원의 효율성 분석 (Analysis of the Efficiency of the Regional Public Hospitals using DEA-AR/AHP Combined Model)

  • 양동현
    • 보건행정학회지
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    • 제20권4호
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    • pp.74-96
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    • 2010
  • The purpose of this empirical study is to evaluate efficiency of the regional public hospitals, using DEA(Data Envelopment Analysis). to do this, we design a DEA-AR/AHP Hybrid model to evaluate efficiency of 34 Regional Public Hospitals. the proposed model is developed by adding Acceptance Region(AR). using analytical hierarchy process(AHP). this model is compared with those of typical DEA models. Financial data used in this study were obtained from Database of the Korea Association Regional Public Hospital and analyzed using DEA model. As a result of analysis, This study found that the DEA-AR/AHP Hybrid model was superior to those typical DEA models in determining the priority among efficient hospitals. the result of this study can provide helpful information to evaluate the efficiency of public hospitals for efficient operational management, to develop more precise measurement for the priority of the efficient hospitals.

자료포락분석(DEA)을 이용한 효율성 측정 - 지방공사 의료원을 대상으로 - (Measuring production efficiency using Data Envelopment Analysis : The case of public Corporation Medical Centers)

  • 박창제
    • 보건행정학회지
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    • 제6권2호
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    • pp.91-114
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    • 1996
  • In this research, the Data Envelopment Analysis(DEA) was applied to measure production efficiency of Public Corporation Medical Centers(PCMCs) operating in Korea. The focus of this research is triple. First, identifing convenience and usefulness of DEA to measure the relative efficiency among PCMCs. Second, assessing magnitudes of the relative efficiency for each PCMC. Third, adding insights into some factors resulting inefficiency in PCMCs. Then, in this paper technical efficiency and scale efficiency measured by DEA[introduced by Charnes, Cooper, and Rhoides(1978) and Banker, Charnes, and Cooper(1984)] were analyzed and a new separate variable was introduced which makes it possible to determine whether operations were conducted in regions of increasing, constant or decresing returns to scale(in multiple input and output situations). And a multi-factor Tobit analysis was conducted to see which variables are associated with PCMC's efficiency.

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지루함, 공적 자의식, 스타일 지향성이 인터넷 구매에 미치는 영향 (The influences of boredom proneness, public self-consciousness, and dressing style on internet shopping)

  • 박혜정
    • 복식문화연구
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    • 제23권5호
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    • pp.876-893
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    • 2015
  • The purpose of this study is to identify the influences of psychological variables and fashion-related psychological variables on purchasing fashion items on the Internet. Boredom proneness and public self-consciousness were selected as psychological variables, and dressing style was selected as a fashion-related psychological variable. It was hypothesized that boredom proneness and public self-consciousness not only influence the purchasing frequency of fashion items on the Internet directly, but also indirectly through dressing style. Data were gathered by surveying university students in Seoul using convenience sampling. Two hundred and eighty-six questionnaires were used in the statistical analysis. SPSS was used for exploratory factor analysis, and AMOS was used for hypothesized relationship testing. The factor analysis of boredom proneness revealed five dimensions, "helplessness," "affective response," "lack of internal stimulation," "lack of external stimulation," and "perception of time." The factor analysis of public self-consciousness revealed two dimensions, "appearance-consciousness" and "style-consciousness," and the factor analysis of dressing style revealed one dimension. The overall fit of the hypothesized model suggests that the model fits the data well. The hypothesized relationship test proved that boredom proneness and public self-consciousness influence the purchasing frequency of fashion items on the Internet indirectly through dressing style. The results implicate effective strategies for Internet shopping malls and suggestions for future study.

클라우드 기반의 공개의료 빅데이터 분석을 통한 삶의 질에 영향을 미치는 요인분석 (An Analysis of Factors Affecting Quality of Life through the Analysis of Public Health Big Data)

  • 김민경;조영복
    • 한국정보통신학회논문지
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    • 제22권6호
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    • pp.835-841
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    • 2018
  • 본 연구에서 공개 의료 빅데이터 분석을 지역사회건강조사 2012~2014년 자료를 이용해 개인의 건강관련 삶의 질 차이와 삶의 질에 영향을 미치는 요인을 분석하였다. 제안논문에서는 공개의료 빅데이터 분석을 위해 Hadoop 기반의 Spack을 이용해 병렬처리 지원을 위한 클라우드 메니저를 구성하고 개인의 삶의 질에 영향을 미치는 요인을 하드웨어의 제약없이 빠르게 분석하였다. 건강관련 삶의 질에 미치는 영향을 개인적 특성과 지역사회 특성으로 구분하여 단계별 다수준 회귀분석(ANOVA, t-test)을 실시하였다. 연구결과 개인별 삶의 질에 영향을 미치는 요인으로는 남자 평균 73.8점, 여자 평균 70.0점으로 남자가 여자보다 건강관련 삶의 질이 높은 것으로 나타났다.

A Study on the General Public's Perceptions of Dental Fear Using Unstructured Big Data

  • Han-A Cho;Bo-Young Park
    • 치위생과학회지
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    • 제23권4호
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    • pp.255-263
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    • 2023
  • Background: This study used text mining techniques to determine public perceptions of dental fear, extracted keywords related to dental fear, identified the connection between the keywords, and categorized and visualized perceptions related to dental fear. Methods: Keywords in texts posted on Internet portal sites (NAVER and Google) between 1 January, 2000, and 31 December, 2022, were collected. The four stages of analysis were used to explore the keywords: frequency analysis, term frequency-inverse document frequency (TF-IDF), centrality analysis and co-occurrence analysis, and convergent correlations. Results: In the top ten keywords based on frequency analysis, the most frequently used keyword was 'treatment,' followed by 'fear,' 'dental implant,' 'conscious sedation,' 'pain,' 'dental fear,' 'comfort,' 'taking medication,' 'experience,' and 'tooth.' In the TF-IDF analysis, the top three keywords were dental implant, conscious sedation, and dental fear. The co-occurrence analysis was used to explore keywords that appear together and showed that 'fear and treatment' and 'treatment and pain' appeared the most frequently. Conclusion: Texts collected via unstructured big data were analyzed to identify general perceptions related to dental fear, and this study is valuable as a source data for understanding public perceptions of dental fear by grouping associated keywords. The results of this study will be helpful to understand dental fear and used as factors affecting oral health in the future.