• 제목/요약/키워드: Quantitative Text Analysis

검색결과 146건 처리시간 0.026초

사회과학을 위한 양적 텍스트 마이닝: 이주, 이민 키워드 논문 및 언론기사 분석 (Quantitative Text Mining for Social Science: Analysis of Immigrant in the Articles)

  • 이수정;최두영
    • 한국콘텐츠학회논문지
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    • 제20권5호
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    • pp.118-127
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    • 2020
  • 본 연구는 최근 사회과학에서 실시되고 있는 양적 텍스트 분석의 흐름과 분석을 실시함에 있어 주의해야 할 사례를 포함하여 기술 하였다. 특히, 2017년부터 2019년까지 3년간 학술지와 언론에서 사용된 "이주", "이민" 키워드를 기반으로 사례연구를 실시하였다. 이를 위해 최근 사회과학분야에서 주목 받는 자연어 처리 기술(NLP)를 이용한 양적 텍스트 분석 (Quantitate text analysis)을 사용하였다. 양적 텍스트 분석은 문서를 구조적 데이터로 변환하여, 가설의 발견 및 검증을 실시하는 데이터 과학의 영역으로, 데이터의 모델링 및 가시화 등이 가능하고, 특히 비구조화 된 데이터를 구조화할 수 있다는 점에서 사회과학 분야에 많이 도입하였다. 따라서 본 연구는 양적 텍스트 분석을 통해 "이주", "이민"을 키워드로 한 연구 및 언론 기사에 대한 통계 분석을 실시하고 도출된 결론에 대한 해석을 실시하였다.

계량적 접근에 의한 조선시대 필사본 조리서의 유사성 분석 (A Quantitative Approach to a Similarity Analysis on the Culinary Manuscripts in the Chosun Periods)

  • 이기황;이재윤;백두현
    • 한국언어정보학회지:언어와정보
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    • 제14권2호
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    • pp.131-157
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    • 2010
  • This article reports an attempt to perform a similarity analysis on a collection of 25 culinary manuscripts in Chosun periods using a set of quantitative text analysis methods. Historical culinary texts are valuable resources for linguistic, historic, and cultural studies. We consider the similarity of two texts as the distributional similarities of the functional components of the texts. In the case of culinary texts, text elements such as food names, cooking methods, and ingredients are regarded as functional components. We derive the similarity information from the distributional characteristics of the two key functional components, cooking methods and ingredients. The results are also quantified and visualized to achieve a better understanding of the properties of the individual texts and the collection of the texts as a whole.

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국내 전자정부 연구동향에 대한 정량적 분석: 텍스트 마이닝과 네트워크 분석 기법을 중심으로 (Quantitative Analysis of Research Trends in Korean E-Government Using Text Mining and Network Analysis Methods)

  • 이수인;신신애;강동석;김상현
    • 정보화정책
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    • 제25권4호
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    • pp.84-107
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    • 2018
  • 기존에 수행된 국내 전자정부 동향연구는 정성적 연구방법에만 의존하는 약점을 지니고 있다. 이에 본 연구는 2018년 9월 현재 시점에서 1996~2017년까지의 데이터를 기반으로 정량적 분석을 수행하였다. 텍스트 마이닝을 통해 도출된 연구주제는 총 7가지였으며, 그중에서도 프레임워크와 공공정책 효과의 네트워크 중심성이 높은 것으로 식별되었다. 본 연구결과는 전자정부의 발전을 위해 필요한 학술적/정책적 시사점을 제공하였다. 시사점 중의 하나는 기존 연구가 주로 수행하던 방식인 정성적 분석방법 대신에 정량적 분석방법을 활용하여, 상대적으로 객관성 및 학문의 다양성 확보에 이바지한다는 점이다.

Phonetic Transcription Rules and Quantitative Analysis of Phoneme Distribution in French

  • Bae, Hee-Sook;Yun, Young-Sun;Oh, Yung-Hwan
    • 음성과학
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    • 제9권1호
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    • pp.149-171
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    • 2002
  • After establishing the rules for the phonetic transcription in French, quantitative analysis on the given text, Waiting for Godot, is performed. Analyzing the text by investigating the influence of phoneme distribution is very interesting in the phonostylistic point of view. Since the phonetic transcription rules are useful for its automation, the rules are carefully established in this paper. From the results of the phonetic transcription, we can investigate the distribution of individual phonemes and the different phoneme groups between dialogues and scenery indications for various characters.

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텍스트마이닝을 활용한 건설분야 트랜드 분석 (Analysis of trend in construction using textmining method)

  • 정철우;김재준
    • 한국디지털건축인테리어학회논문집
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    • 제12권2호
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    • pp.53-60
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    • 2012
  • In this paper, we present new methods for identifying keywords for foresight topics that utilize the internet and textmining techniques to draw objective and quantified information that support experts' qualitative opinions and evaluations in foresight. Furthermore, by applying this fabricated procedure, we have derived keywords to analyze priorities in architectural engineering. Not much difference between qualitative methods of experts and quantitative methods such as text mining has been observed from comparison between technologies derived via qualitative method from "The Science Technology Vision" (control group). Therefore, as a quantitative tool useful for drawing keywords for foresight, textmining can supplement quantitative analysis by experts. In addition, depending on the level and type of raw data, text mining can bring better results in deriving foresight keywords. For this reason, research activities accommodating Internet search results and the development of textmining methods for analyzing current trends are in demand.

Investigating the Value of Information in Mobile Commerce: A Text Mining Approach

  • Wang, Ying;Aguirre-Urreta, Miguel;Song, Jaeki
    • Asia pacific journal of information systems
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    • 제26권4호
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    • pp.577-592
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    • 2016
  • The proliferation of mobile applications and the unique characteristics of the mobile environment have attracted significant research interest in understanding customers' purchasing behaviors in mobile commerce. In this study, we extend customer value theory by combining the predictors of product performance with customer value framework to investigate how in-store information creates value for customers and influences mobile application downloads. Using a data set collected from the Google Application Store, we find that customers value both text and non-text information when they make downloading decisions. We apply latent semantic analysis techniques to analyze customer reviews and product descriptions in the mobile application store and determine the embedded valuable information. Results show that, for mobile applications, price, number of raters, and helpful information in customer reviews and product descriptions significantly affect the number of downloads. Conversely, average rating does not work in the mobile environment. This study contributes to the literature by revealing the role of in-store information in mobile application downloads and by providing application developers with useful guidance about increasing application downloads by improving in-store information management.

과학교과서 텍스트의 계량적 분석을 이용한 과학 개념어의 생산적 지식 교육 방안 탐색 (Exploring Teaching Method for Productive Knowledge of Scientific Concept Words through Science Textbook Quantitative Analysis)

  • 윤은정
    • 한국과학교육학회지
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    • 제40권1호
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    • pp.41-50
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    • 2020
  • 과학 개념에 대한 이해를 언어학적 관점에서 바라보면 학생들이 과학 개념어에 대한 깊고 정교한 이해와 더불어 정확하게 사용할 수 있는 능력을 길러주는 것이 매우 중요하다. 본 연구에서는 지금까지 과학 교육에서 과학 개념어에 대한 생산적 지식 교육의 기틀이 잘 마련되어 있지 않음에 주목하고, 과학 개념을 구성하고 있는 단어들 사이의 관계를 생산적이고 효과적으로 교육할 수 있는 방안을 탐색함으로써 과학 개념어의 생산적 지식 교육의 기틀을 제공하고자 하였다. 이를 위해 첫째, 몇 가지의 계량 언어학적 텍스트 분석 방법을 이용하여 과학 교과서 텍스트로 부터 과학 개념을 구성하고 있는 단어들과 그들 사이의 관계를 추출하고, 둘째, 각 방법의 결과로 추출된 단어 관계의 의미를 정성적으로 살펴본 뒤, 셋째, 이를 이용하여 과학 개념어의 생산적 지식 향상에 도움을 줄 수 있는 쓰기 활동 방법을 제안해 보았다. 중학교 1학년 과학교과서 '힘과 운동' 단원 텍스트를 클러스터 분석, 공기 빈도 분석, 텍스트 네트워크 분석, 그리고 워드임베딩의 네 가지 계량 언어학적 분석 방법을 사용하여 분석해 보았다. 연구 결과 첫째, 클러스터 분석 결과를 활용하여 문장 완성하기 활동을 제안하였다. 둘째, 공기 빈도 분석 결과를 이용한 빈 칸 채우기 활동을 제안하였다. 셋째, 네트워크 분석 결과를 이용하여 소재 중심 글쓰기 활동을 제안하였다. 넷째, 워드임베딩을 이용한 학습 중요 단어 목록 작성을 제안하였다.

Is Text Mining on Trade Claim Studies Applicable? Focused on Chinese Cases of Arbitration and Litigation Applying the CISG

  • Yu, Cheon;Choi, DongOh;Hwang, Yun-Seop
    • Journal of Korea Trade
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    • 제24권8호
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    • pp.171-188
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    • 2020
  • Purpose - This is an exploratory study that aims to apply text mining techniques, which computationally extracts words from the large-scale text data, to legal documents to quantify trade claim contents and enables statistical analysis. Design/methodology - This is designed to verify the validity of the application of text mining techniques as a quantitative methodology for trade claim studies, that have relied mainly on a qualitative approach. The subjects are 81 cases of arbitration and court judgments from China published on the website of the UNCITRAL where the CISG was applied. Validation is performed by comparing the manually analyzed result with the automatically analyzed result. The manual analysis result is the cluster analysis wherein the researcher reads and codes the case. The automatic analysis result is an analysis applying text mining techniques to the result of the cluster analysis. Topic modeling and semantic network analysis are applied for the statistical approach. Findings - Results show that the results of cluster analysis and text mining results are consistent with each other and the internal validity is confirmed. And the degree centrality of words that play a key role in the topic is high as the between centrality of words that are useful for grasping the topic and the eigenvector centrality of the important words in the topic is high. This indicates that text mining techniques can be applied to research on content analysis of trade claims for statistical analysis. Originality/value - Firstly, the validity of the text mining technique in the study of trade claim cases is confirmed. Prior studies on trade claims have relied on traditional approach. Secondly, this study has an originality in that it is an attempt to quantitatively study the trade claim cases, whereas prior trade claim cases were mainly studied via qualitative methods. Lastly, this study shows that the use of the text mining can lower the barrier for acquiring information from a large amount of digitalized text.

텍스트 마이닝을 활용한 사용자 핵심 요구사항 분석 방법론 : 중국 온라인 화장품 시장을 중심으로 (A Methodology for Customer Core Requirement Analysis by Using Text Mining : Focused on Chinese Online Cosmetics Market)

  • 신윤식;백동현
    • 산업경영시스템학회지
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    • 제44권2호
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    • pp.66-77
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    • 2021
  • Companies widely use survey to identify customer requirements, but the survey has some problems. First of all, the response is passive due to pre-designed questionnaire by companies which are the surveyor. Second, the surveyor needs to have good preliminary knowledge to improve the quality of the survey. On the other hand, text mining is an excellent way to compensate for the limitations of surveys. Recently, the importance of online review is steadily grown, and the enormous amount of text data has increased as Internet usage higher. Also, a technique to extract high-quality information from text data called Text Mining is improving. However, previous studies tend to focus on improving the accuracy of individual analytics techniques. This study proposes the methodology by combining several text mining techniques and has mainly three contributions. Firstly, able to extract information from text data without a preliminary design of the surveyor. Secondly, no need for prior knowledge to extract information. Lastly, this method provides quantitative sentiment score that can be used in decision-making.

텍스트마이닝을 활용한 사용자 요구사항 우선순위 도출 방법론 : 온라인 게임을 중심으로 (Analysis of User Requirements Prioritization Using Text Mining : Focused on Online Game)

  • 정미연;허선우;백동현
    • 산업경영시스템학회지
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    • 제43권3호
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    • pp.112-121
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    • 2020
  • Recently, as the internet usage is increasing, accordingly generated text data is also increasing. Because this text data on the internet includes users' comments, the text data on the Internet can help you get users' opinion more efficiently and effectively. The topic of text mining has been actively studied recently, but it primarily focuses on either the content analysis or various improving techniques mostly for the performance of target mining algorithms. The objective of this study is to propose a novel method of analyzing the user's requirements by utilizing the text-mining technique. To complement the existing survey techniques, this study seeks to present priorities together with efficient extraction of customer requirements from the text data. This study seeks to identify users' requirements, derive the priorities of requirements, and identify the detailed causes of high-priority requirements. The implications of this study are as follows. First, this study tried to overcome the limitations of traditional investigations such as surveys and VOCs through text mining of online text data. Second, decision makers can derive users' requirements and prioritize without having to analyze numerous text data manually. Third, user priorities can be derived on a quantitative basis.