• Title/Summary/Keyword: 동시출현단어 분석

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Comparative Analysis of Low Fertility Policy and the Public Perceptions using Text-Mining Methodology (텍스트 마이닝을 활용한 저출산 정책과 대중인식 비교)

  • Bae, Giryeon;Moon, HyunJeong;Lee, Jaeil;Park, Mina;Park, Arum
    • Journal of Digital Convergence
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    • v.19 no.12
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    • pp.29-42
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    • 2021
  • As the low fertility intensifies in Korea, this study investigated fundamental differences between the government's low fertility policy and public perception of it. To this end, we selected four times 'Aging Society and Population Policy' documents and news comments for two weeks immediately after announcement of the third and fourth Policy as analysis targets. Then we conducted word frequency analysis, co-occurrence analysis and CONCOR analysis. As a result of analyses, first, direct childcare support during the first and second periods, and a social structural approach during third and fourth periods were noticeable. Second, it was revealed that both policies and comments aim for the work-family compatibility in 'parenting'. Lastly it was showed public interest in environment of raising children and the critical mind to effectiveness of the policy. This study is meaningful in that it confirmed the public perception using big data analysis, and it will help improve the direction for the future low fertility policy.

A Method for Compound Noun Extraction to Improve Accuracy of Keyword Analysis of Social Big Data

  • Kim, Hyeon Gyu
    • Journal of the Korea Society of Computer and Information
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    • v.26 no.8
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    • pp.55-63
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    • 2021
  • Since social big data often includes new words or proper nouns, statistical morphological analysis methods have been widely used to process them properly which are based on the frequency of occurrence of each word. However, these methods do not properly recognize compound nouns, and thus have a problem in that the accuracy of keyword extraction is lowered. This paper presents a method to extract compound nouns in keyword analysis of social big data. The proposed method creates a candidate group of compound nouns by combining the words obtained through the morphological analysis step, and extracts compound nouns by examining their frequency of appearance in a given review. Two algorithms have been proposed according to the method of constructing the candidate group, and the performance of each algorithm is expressed and compared with formulas. The comparison result is verified through experiments on real data collected online, where the results also show that the proposed method is suitable for real-time processing.

A Comparison of Current Trends in Soil Erosion Research Using Keyword Co-occurrence Analysis (동시출현단어 분석을 이용한 토양침식 연구동향 비교 분석)

  • Lim, Young-Hyup;Kim, Suk-Woo;Nam, Sooyoun;Chun, Kun-Woo;Kim, Minseok
    • Korean Journal of Environment and Ecology
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    • v.34 no.5
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    • pp.413-424
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    • 2020
  • Environmental policies and industry practices have recently seen a gradual paradigm shift from reactive management to proactive prevention of environmental impacts. Accordingly, preventive conservation policies are carried out to address the increasing value of protecting soils and soil functions as resources are limited. To propose a direction for future soil erosion research, we analyzed domestic and international research trends of soil erosion, based on journal papers retrieved from the Web of Science databases over the last decade, using VOSviewer for keyword co-occurrence analysis. The results showed that the number of publications on soil erosion per land area in Korea ranked high worldwide. In particular, studies on the soil erosion control were found to account for a more significant proportion than other countries. The active ongoing studies on soil erosion in Korea indicate that the country has recognized the severity of soil erosion resulting from climate, topography, and land use. However, the number of keywords found in the studies on the soil erosion control in Korea was relatively smaller than those found at the international level, indicating the need to diversify and expand the study subjects. In particular, studies on the soil erosion process and the related physical and chemical soil properties are necessary to find the fundamental solutions to soil erosion problems.

A Bibliometric Analysis of Research Trends on Disaster in Korea (국내 재난 관련 연구 동향에 대한 계량정보학적 분석)

  • Lee, Jae Yun;Kim, Soojung
    • Journal of the Korean Society for information Management
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    • v.33 no.4
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    • pp.103-124
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    • 2016
  • This study aims to investigate the research trends of disaster in Korea through a bibliometric analysis. To do that, it analyzed 772 scholarly articles published from 2002 to 2016, retrieved from KCI (Korean Citation Index) database. For analysis, discipline profiling analysis, journal profiling analysis, and co-word analysis methods were used. The study found that the number of scholarly articles on disaster has increased, especially after Sewol ferry disaster occurred in 2004. The major discipline areas were identified as 'policy sciences/public administration' area, 'engineering' area, 'GIS/telecommunication' area, and 'medical/humanities/social sciences' area. In terms of time series, the proportion of scholarly articles published in 'policy sciences/public administration' area has decreased since 2014 and at the same time, discipline areas have been diversified including law, medical, and journalism.

Text Mining Driven Content Analysis of Ebola on News Media and Scientific Publications (텍스트 마이닝을 이용한 매체별 에볼라 주제 분석 - 바이오 분야 연구논문과 뉴스 텍스트 데이터를 이용하여 -)

  • An, Juyoung;Ahn, Kyubin;Song, Min
    • Journal of the Korean Society for Library and Information Science
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    • v.50 no.2
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    • pp.289-307
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    • 2016
  • Infectious diseases such as Ebola virus disease become a social issue and draw public attention to be a major topic on news or research. As a result, there have been a lot of studies on infectious diseases using text-mining techniques. However, there is no research on content analysis of two media channels that have distinct characteristics. Accordingly, in this study, we conduct topic analysis between news (representing a social perspective) and academic research paper (representing perspectives of bio-professionals). As text-mining techniques, topic modeling is applied to extract various topics according to the materials, and the word co-occurrence map based on selected bio entities is used to compare the perspectives of the materials specifically. For network analysis, topic map is built by using Gephi. Aforementioned approaches uncovered the difference of topics between two materials and the characteristics of the two materials. In terms of the word co-occurrence map, however, most of entities are shared in both materials. These results indicate that there are differences and commonalties between social and academic materials.

An Investigation on Characteristics and Intellectual Structure of Sociology by Analyzing Cited Data (사회학 분야의 연구데이터 특성과 지적구조 규명에 관한 연구)

  • Choi, Hyung Wook;Chung, EunKyung
    • Journal of the Korean Society for information Management
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    • v.34 no.3
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    • pp.109-124
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    • 2017
  • Through a wide variety of disciplines, practices on data access and re-use have been increased recently. In fact, there has been an emerging phenomenon that researchers tend to use the data sets produced by other researchers and give scholarly credit as citation. With respect to this practice, in 2012, Thomson Reuters launched Data Citation Index (DCI). With the DCI, citation to research data published by researchers are collected and analyzed in a similar way for citation to journal articles. The purpose of this study is to identify the characteristics and intellectual structure of sociology field based on research data, which is one of actively data-citing fields. To accomplish this purpose, two data sets were collected and analyzed. First, from DCI, a total of 8,365 data were collected in the field of sociology. Second, a total of 12,132 data were collected from Web of Science with a topic search with 'Sociology'. As a result of the co-word analysis of author provided-keywords for both data sets, the intellectual structure of research data-based sociology was composed of two areas and 15 clusters and that of article-based sociology was composed with three areas and 17 clusters. More importantly, medical science area was found to be actively studied in research data-based sociology and public health and psychology are identified to be central areas from data citation.

Web Site Keyword Selection Method by Considering Semantic Similarity Based on Word2Vec (Word2Vec 기반의 의미적 유사도를 고려한 웹사이트 키워드 선택 기법)

  • Lee, Donghun;Kim, Kwanho
    • The Journal of Society for e-Business Studies
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    • v.23 no.2
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    • pp.83-96
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    • 2018
  • Extracting keywords representing documents is very important because it can be used for automated services such as document search, classification, recommendation system as well as quickly transmitting document information. However, when extracting keywords based on the frequency of words appearing in a web site documents and graph algorithms based on the co-occurrence of words, the problem of containing various words that are not related to the topic potentially in the web page structure, There is a difficulty in extracting the semantic keyword due to the limit of the performance of the Korean tokenizer. In this paper, we propose a method to select candidate keywords based on semantic similarity, and solve the problem that semantic keyword can not be extracted and the accuracy of Korean tokenizer analysis is poor. Finally, we use the technique of extracting final semantic keywords through filtering process to remove inconsistent keywords. Experimental results through real web pages of small business show that the performance of the proposed method is improved by 34.52% over the statistical similarity based keyword selection technique. Therefore, it is confirmed that the performance of extracting keywords from documents is improved by considering semantic similarity between words and removing inconsistent keywords.

Analysis of Research Trends in the Hydrogen Energy Field Using Co-Occurrence Keyword Analysis (동시출현 핵심단어 분석을 활용한 수소 에너지 관련 연구동향 분석)

  • Kim, Minju;Kwon, Sangki
    • Explosives and Blasting
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    • v.40 no.3
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    • pp.1-18
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    • 2022
  • Due to the advent of the hydrogen economy era, various studies are being conducted to transport and store hydrogen, and the risk of hydrogen explosion is emerging. In order to figure out the new technology related to hydrogen energy, it is necessary to figure out the overall research trends related to various hydrogen energy at home and abroad. In this study, a bibliometric analysis using VOSViewer for the papers published in the international journal was conducted. From the analysis in different time period using the keywords including hydrogen explosion, hydrogen pipeline, and hydrogen storage, it was found that there were frequent paper publications using numerical analysis simulation. It is also found that more and more researches on safety and hydrogen explosion in hydrogen storage and hydrogen pipeline transportation have been conducted in 2011-2022 compared to those in 2000-2010.

Analyzing the Study Trends of 'Sense of Place' Using Text Mining Techniques (텍스트마이닝 기법을 활용한 국내외 장소성 관련 연구동향 분석)

  • Lee, Ina;Kim, Hea-Jin
    • Journal of the Korean BIBLIA Society for library and Information Science
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    • v.30 no.2
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    • pp.189-209
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    • 2019
  • Main Path Analysis (MPA) is one of the text mining techniques that extracts the core literature that contributes knowledge transfer based on citation information in the literature. This study applied various text mining techniques to abstract of the paper related with sense-of-place, which is published at Korea and abroad from 1990 to 2018 so that could discuss in a macro perspective. The main path analysis results showed that from 1990, overseas research on sense-of-place has been carried out in the order of personal identity, public land management, environmental education and urban development-related areas. Also, by using the network analysis, this study found that sense-of-place was discussed at various levels in Korea, including urban development, culture, literature, and history. On the other hand, it has been found that there are few topic changes in international studies, and that discussions on health, identity, landscape and urban development have been going on steadily since the 1990s. This study has implications that it presents a new perspective of grasping the overall flow of relevant research.

A Study on the Perception of Pit and Fissure Sealant using Unstructured Big Data (비정형 빅데이터를 이용한 치면열구전색(치아홈메우기)에 대한 인식분석)

  • Han-A Cho
    • Journal of Korean Dental Hygiene Science
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    • v.6 no.2
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    • pp.101-114
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    • 2023
  • Background: This study aimed to explore the overall perception of pit and fissure sealants and suggest methods to revitalize their current stagnation. Methods: To determine the social perception of the change in coverage policy for pit and fissure sealants, we categorized them into five time periods. The first period (December 1, 2009 to November 30, 2010), the second period (December 1, 2010 to September 30, 2012), the third period (October 1, 2012 to May 5, 2013), the fourth period (May 6, 2013 to September 30, 2017), and the fifth period (October 1, 2017 to December 31, 2022). We utilized text mining, an unstructured big data analysis method. Keywords were collected and analyzed using Textom, and the frequency analysis of the top 30 keywords, structural features of the semantic network, centrality analysis, QAP correlation analysis, and co-occurrence analysis were conducted. Results: The frequency analysis showed that the top keywords for each time period were 'Cavities', 'Treatment', and 'Children'. In the structural features of the semantic network of pit and fissure sealants by time period, the density index was found to be around 1.00 for all time periods. The QAP correlation analysis showed the highest correlation between the first and second periods and the fourth and fifth periods with a correlation coefficient of 0.834. The co-occurrence analysis showed that 'cavities' and 'prevention were the top two words across all time periods. Conclusion: This study showed that pit and fissure sealants are well accepted by the society as a preventive treatment for caries. However, the awareness of health education related to these sealants was found to be low. Efforts to revitalize stagnant pit and fissure sealants need to be strengthened with effective education.