• Title/Summary/Keyword: 텍스트 연구

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Aspect-based Sentiment Analysis on Cosmetics Customer Reviews (감성 분석 화장품 사용자 리뷰에 대한 속성기반 감성분석)

  • Heewon Jeong;Young-Seob Jeong
    • Proceedings of the Korean Society of Computer Information Conference
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    • 2024.01a
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    • pp.13-16
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    • 2024
  • 온라인상에 인간의 감성을 담은 리뷰 데이터가 꾸준히 축적되어왔다. 이 텍스트 데이터를 분석하고 활용하는 일은 마케팅에 있어서 중요한 자산이 될 것이다. 이와 관련된 Aspect-Based Sentiment Analysis(ABSA) 연구는 한글에 있어서는 데이터 부족을 이유로 거의 선행연구가 없는 실정이다. 본 연구에서는 최근 공개된 데이터 셋을 바탕으로 하여 화장품 도메인에 대한 소비자들의 리뷰 텍스트와 사전 라벨링 된 속성, 감성 극성을 기반으로 ABSA를 진행한다. Klue RoBERTa base 모델을 활용하여 데이터를 학습시키고, Python Kiwipiepy 등으로 전처리한 결과를 대시보드로 시각화하여 분석하기 쉬운 환경을 마련하는 방법을 제시한다.

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'Economic Security' Discourse Analysis Using Text Mining (텍스트 마이닝을 활용한 '경제안보' 담론 분석)

  • Jungjoo Oh;Yeram Lim;Hyesu Cheon;Wonhyung Park
    • Annual Conference of KIPS
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    • 2024.05a
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    • pp.513-516
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    • 2024
  • 미·중 기술 패권 경쟁이 심화되면서 경제안보는 국가안보의 핵심 요소로 부상하였다. 주요국들은 각국이 도입한 경제안보 개념에 따라 입법과 정책을 추진하고 있다. 그러나 우리나라에서 경제안보 개념은 아직까지 불분명한 상황이다. 이에 본 연구는 국내 뉴스 빅데이터를 통해 경제안보 관련 담론을 파악하여 한국식 경제안보 개념화를 위한 토대를 만드는 것을 목적으로 하였다. 빅카인즈를 통해 경제안보 관련 뉴스 기사를 수집하고 텍스트 마이닝을 활용하여 분석하였다. TF-IDF 분석과 LDA 토픽 모델링이 분석에 활용되었다. 그 결과 세 개의 주요 토픽이 도출되었고, 경제안보의 이중 구조를 확인할 수 있었다. 본 연구는 향후 한국식 경제안보를 개념화하고 그에 대한 전략을 마련하기 위한 기초자료로 활용할 수 있을 것으로 기대한다.

The Study on Educational Countermeasures Through AI Analysis of Spam Message Data (스팸 문자 데이터의 인공지능 분석을 통한 교육적 대처 방안 연구)

  • Subeen Lim;Moohong Min
    • Annual Conference of KIPS
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    • 2024.10a
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    • pp.69-72
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    • 2024
  • 최근 스팸 문자 메시지의 급증은 사용자들에게 심각한 불편을 초래할 뿐만 아니라, 불법 도박 및 금융 사기와 같은 중대한 사회적 문제로 이어지고 있다. 본 연구는 이러한 스팸 문자 메시지의 패턴과 텍스트를 심층적으로 분석하여, 스팸 메시지의 경향을 파악하고 청소년 도박 문제에 대한 교육적 대처 방안을 도출하는 것을 목표로 한다. 2022년 8월부터 2024년 3월까지 약 1년 7개월 동안 신고된 스팸 문자 데이터를 바탕으로, 스팸 메시지의 신고량 추이와 키워드 군집 분포를 분석하였다. 분석 결과, 스팸 메시지는 주로 주중 방과 후 시간대인 12시에서 18시 사이에 집중되었으며, 도박 관련 스팸 메시지가 전체의 62.7%로 가장 큰 비중을 차지하였다. 텍스트 분석을 통해 도출된 주요 키워드는 신규 가입 유도 및 금전적 유인과 관련된 것으로, 청소년들이 도박에 유인될 가능성이 높은 요소들이 포함된 것으로 분석되었다. 본 연구는 스팸 문자 데이터의 인공지능 분석을 통해 청소년 도박 문제에 대한 중요한 시사점을 제공한다.

Research Trends Investigation Using Text Mining Techniques: Focusing on Social Network Services (텍스트마이닝을 활용한 연구동향 분석: 소셜네트워크서비스를 중심으로)

  • Yoon, Hyejin;Kim, Chang-Sik;Kwahk, Kee-Young
    • Journal of Digital Contents Society
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    • v.19 no.3
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    • pp.513-519
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    • 2018
  • The objective of this study was to examine the trends on social network services. The abstracts of 308 articles were extracted from web of science database published between 1994 and 2016. Time series analysis and topic modeling of text mining were implemented. The topic modeling results showed that the research topics were mainly 20 topics: trust, support, satisfaction model, organization governance, mobile system, internet marketing, college student effect, opinion diffusion, customer, information privacy, health care, web collaboration, method, learning effectiveness, knowledge, individual theory, child support, algorithm, media participation, and context system. The time series regression results indicated that trust, support satisfaction model, and remains of the topics were hot topics. This study also provided suggestions for future research.

An Exploratory Study of VR Technology using Patents and News Articles (특허와 뉴스 기사를 이용한 가상현실 기술에 관한 탐색적 연구)

  • Kim, Sungbum
    • Journal of Digital Convergence
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    • v.16 no.11
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    • pp.185-199
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    • 2018
  • The purpose of this study is to derive the core technologies of VR using patent analysis and to explore the direction of social and public interest in VR using news analysis. In Study 1, we derived keywords using the frequency of words in patent texts, and we compared by company, year, and technical classification. Netminer, a network analysis program, was used to analyze the IPC codes of patents. In Study 2, we analyzed news articles using T-LAB program. TF-IDF was used as a keyword selection method and chi-square and association index algorithms were used to extract the words most relevant to VR. Through this study, we confirmed that VR is a fusion technology including optics, head mounted display (HMD), data analysis, electric and electronic technology, and found that optical technology is the central technology among the technologies currently being developed. In addition, through news articles, we found that the society and the public are interested in the formation and growth of VR suppliers and markets, and VR should be developed on the basis of user experience.

A Narrative Inquiry on the Retired Elderly Person's Library Use Experience (은퇴노인의 도서관 이용 경험에 관한 내러티브 탐구)

  • Lee, Hosin
    • Journal of the Korean Society for information Management
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    • v.36 no.1
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    • pp.215-246
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    • 2019
  • The purpose of this study is to comprehend the retired elderly person's experience of library using the narrative inquiry method proposed by Clandinin and Cornelly. I intended to grasp the details of the several changes that library use brings to the lives. It was also to examine the meanings of the experiences for their lives. For this purpose, three elderly retirees using public libraries in Seoul were selected as research participants. I interviewed their experiences and constructed field text from interview. Based on the field text, the story of the participants was reconstructed into research text which is form of novels, essays, and letters. Their experience in using libraries was interpreted as a source of regular life, fun and vitality, a treasure house for dreaming new life, a source of consolation to endure old age. And I found some common points within their narrative that they seek for a healthy life through reading books. The results of this study are expected to be useful for expanding the understanding of the public library's elderly users and to be used as basic data for service improvement.

Analyzing Game Streaming Application Reviews Using Text Mining Approach: Research to Strengthen Digital Competitiveness (텍스트마이닝 기법을 활용한 게임 스트리밍 애플리케이션 리뷰 분석: 디지털 경쟁력 강화를 위한 연구)

  • Jin, Wenhui;Lee, Jungwoo
    • Journal of Digital Convergence
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    • v.20 no.4
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    • pp.279-290
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    • 2022
  • As the growth of the live streaming service market is accelerating due to COVID-19, the number of downloads and reviews of live streaming mobile applications is also rapidly skyrocketing. This study is to research game streaming applications using Twitch reviews as database. A total of 8 topics are extracted through LDA topic modeling and 7 out of them are detected to be inconvenience factors. Then, to pinpoint the main inconvenience factors, co-occurrence analysis is used in order to find out main factors. Finally, based on previous studies, several solutions are provided, which can solve the inconvenience factors(advertisement, UI design, technology problems) as well as strengthening digital competitiveness. This study will serve as an opportunity to improve digital competitiveness not only for Twitch but also for other game live streaming service companies in the future.

An Exploratory Study of Success Factors for Generative AI Services: Utilizing Text Mining and ChatGPT (생성형AI 서비스의 성공요인에 대한 탐색적 연구: 텍스트 마이닝과 ChatGPT를 활용하여)

  • Ji Hoon Yang;Sung-Byung Yang;Sang-Hyeak Yoon
    • Information Systems Review
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    • v.25 no.2
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    • pp.125-144
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    • 2023
  • Generative Artificial Intelligence (AI) technology is gaining global attention as it can automatically generate sentences, images, and voices that humans previously generated. In particular, ChatGPT, a representative generative AI service, shows proactivity and accuracy differentiated from existing chatbot services, and the number of users is rapidly increasing in a short period of time. Despite this growing interest in generative AI services, most preceding studies are still in their infancy. Therefore, this study utilized LDA topic modeling and keyword network diagrams to derive success factors for generative AI services and to propose successful business strategies based on them. In addition, using ChatGPT, a new research methodology that complements the existing text-mining method, was presented. This study overcomes the limitations of previous research that relied on qualitative methods and makes academic and practical contributions to the future development of generative AI services.

A Study on Perception Analysis and Strategic Direction of Spatial Computing through Text Mining: Focusing on the Case of Apple Vision Pro (텍스트마이닝을 통한 공간 컴퓨팅 인식 분석 및 전략 방향에 관한 연구: 애플 비전 프로 사례를 중심으로)

  • Heetae Yang
    • Information Systems Review
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    • v.26 no.2
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    • pp.205-221
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    • 2024
  • In June 2023, the term "spatial computing" began gaining recognition among the public with Apple's Vision Pro announcement, and interest surged exponentially after its official release in February 2024. With the market opening up, there's a need to analyze public perception for sustainable growth of Spatial Computing and provide evidence-based strategies for industry and government response. This study explores domestic public perception of Spatial Computing using various text mining techniques and seeks strategic directions for successful market penetration based on the analysis. Significantly, the study contributes by leading research on Spatial Computing, proposing new research methodologies, and offering strategic and policy directions for stakeholders.

Changes in mathematics pedagogical lexicons: Extension research of the International Classroom Lexicon using a text mining approach (수학 교수학적 어휘의 변화: 텍스트 마이닝 기법을 이용한 교실수업 어휘 연구의 확장)

  • Lee, Gima;Kim, Hee-jeong
    • The Mathematical Education
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    • v.61 no.4
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    • pp.559-579
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    • 2022
  • Research on lexicon and language provides insights into the interests, values and practices of a community where individuals use the language. The International Classroom Lexicon Project, in which ten countries participated, identified own country's mathematics teaching and learning lexicons by investigating mathematics classroom instruction from teachers' perspectives in a speaking-oriented community. This study, as an extension of the International Classroom Lexicon Project research, investigated pedagogical lexicons used in 「Mathematics and Education」 journals specialized for Korean professional mathematics teachers published by the Korean Society of Teachers of Mathematics. Using the text mining approach, we also traced how these pedegogical lexicons have changed quantitatively over the past 10 years with a diachronic perspective. As a results, several novel terms were found in the writing-oriented community, which were not identified in the speaking-oriented community. In addition, we could discover some pedagogical lexicons have increased statistically significantly and some lexicons appeared(increased) rapidly across years. This implies the teacher community's values and zeitgeist by reflecting these changes in the sociocultural, incidental and social changing (i.e., periodical change) contexts. This study has value as a first step in understanding zeitgeist for mathematics education in Korean mathematics teacher community according to changes of times over the past 10 years. Also, this study contributes to the methodological insights: the text mining technique provides a methodological contribution to researching changes in interests, values and zeitgeist according to these changes in the times.