• Title/Summary/Keyword: 텍스트 연구

Search Result 3,492, Processing Time 0.026 seconds

A Study on the Perception of Fashion Platforms and Fashion Smart Factories using Big Data Analysis (빅데이터 분석을 이용한 패션 플랫폼과 패션 스마트 팩토리에 대한 인식 연구)

  • Song, Eun-young
    • Fashion & Textile Research Journal
    • /
    • v.23 no.6
    • /
    • pp.799-809
    • /
    • 2021
  • This study aimed to grasp the perceptions and trends in fashion platforms and fashion smart factories using big data analysis. As a research method, big data analysis, fashion platform, and smart factory were identified through literature and prior studies, and text mining analysis and network analysis were performed after collecting text from the web environment between April 2019 and April 2021. After data purification with Textom, the words of fashion platform (1,0591 pieces) and fashion smart factory (9750 pieces) were used for analysis. Key words were derived, the frequency of appearance was calculated, and the results were visualized in word cloud and N-gram. The top 70 words by frequency of appearance were used to generate a matrix, structural equivalence analysis was performed, and the results were displayed using network visualization and dendrograms. The collected data revealed that smart factory had high social issues, but consumer interest and academic research were insufficient, and the amount and frequency of related words on the fashion platform were both high. As a result of structural equalization analysis, it was found that fashion platforms with strong connectivity between clusters are creating new competitiveness with service platforms that add sharing, manufacturing, and curation functions, and fashion smart factories can expect future value to grow together, according to digital technology innovation and platforms. This study can serve as a foundation for future research topics related to fashion platforms and smart factories.

A Study on the Construction of a Car Camping Map and Recommendation of Car Camping based on SNS Text Mining Analysis for the Post-Corona Era (SNS 텍스트 마이닝 기반 포스트 코로나 신트렌드 차박 여행 지도 제작 및 차박지 추천에 관한 연구)

  • Kim, Minjeong;Kim, Soohyun;Oh, Jihye;Eom, Jiyoon;Kang, Juyoung
    • Journal of Information Technology Services
    • /
    • v.20 no.5
    • /
    • pp.11-28
    • /
    • 2021
  • As untact travel has become a new trend in leisure culture due to the spread of COVID-19, car camping market is rapidly increasing. The sales of car camping-related goods increased by up to 600 percent, and the sales of SUV in Korea also increased by about four times. Despite the growth of the car camping market, there is a lack of research on the actual condition of the car camping market or research on the user's perspective. Therefore, in this study, a survey of actual camping users was conducted to derive factors that they consider important in camping, and through this, a car camping map was produced. As a result, two types of maps were produced: a map about the car camping site and convenience facilities closest to the car camping site in Gangwon-do, and a hash tag themed map based on keywords for each car camping site. We gathered data on portal sites and social media to obtain information related to camping sites and proceeded with analysis using text mining. In addition, we extracted keywords using network analysis techniques and selected key themes that represent them. This allows the user to choose a car camping site by selecting keywords that suit their taste. We hope that this research will help car camping researchers as a prior study and provide a foundation for leading a clean camping culture through clean camping campaign. Also, we hope that car camping users will be able to do quality trip.

Knowledge Structure of Chronic Obstructive Pulmonary Disease Health Information on Health-Related Websites and Patients' Needs in the Literature Using Text Network Analysis (웹사이트에 제공된 만성폐쇄성폐질환 건강정보와 연구문헌에 나타난 환자의 건강정보 요구의 지식구조: 텍스트 네트워크 분석 활용)

  • Choi, Ja Yun;Lim, Su Yeon;Yun, So Young
    • Journal of Korean Academy of Nursing
    • /
    • v.51 no.6
    • /
    • pp.720-731
    • /
    • 2021
  • Purpose: The purpose of this study was to identify the knowledge structure of health information (HI) for chronic obstructive pulmonary disease (COPD). Methods: Keywords or meaningful morphemes from HI presented on five health-related websites (HRWs) of one national HI institute and four hospitals, as well as HI needs among patients presented in nine literature, were reviewed, refined, and analyzed using text network analysis and their co-occurrence matrix was generated. Two networks of 61 and 35 keywords, respectively, were analyzed for degree, closeness, and betweenness centrality, as well as betweenness community analysis. Results: The most common keywords pertaining to HI on HRWs were lung, inhaler, smoking, dyspnea, and infection, focusing COPD treatment. In contrast, HI needs among patients were lung, medication, support, symptom, and smoking cessation, expanding to disease management. Two common sub-topic groups in HI on HRWs were COPD overview and medication administration, whereas three common sub-topic groups in HI needs among patients in the literature were COPD overview, self-management, and emotional management. Conclusion: The knowledge structure of HI on HRWs is medically oriented, while patients need supportive information. Thus, the support system for self-management and emotional management on HRWs must be informed according to the structure of patients' needs for HI. Healthcare providers should consider presenting COPD patient-centered information on HRWs.

Presentation of Self and SNS Posting Styles: Focusing on Goffman's Impression Management Framework (자아 표현과 SNS 게시 형식: 고프만의 인상관리 이론을 중심으로)

  • Song, Seung-A;Shin, Hyung-Deok
    • The Journal of the Korea Contents Association
    • /
    • v.22 no.4
    • /
    • pp.284-291
    • /
    • 2022
  • People use various tools to present themselves including Social Network Services(SNS hereafter). This study categorized three types of presentation of self, which are genuine, ideal, and social self, and based on Goffman's Impression Management Framework, investigated if these types of presentations have any patterns related to SNS posting styles. Especially, we focused on the styles of hashtags including if hashtags are used in the main tests, if hashtags are hidden, and what kinds of words are used for hashtags. Using 450 posting data uploaded to the Instagram, we found that the posting presenting ideal self show very high rate of using hidden hashtags(98%) and using common expressions(97%), which are not the case for genuine and social self types. This results imply that people concern more about their impressions especially when they present their ideal self on SNS, partially confirming Goffman's Impression Management Framework.

Musical Analysis on the Phrases of Chinese Poetry in Pansori Words (판소리 사설 중 한시 어구의 활용에 따른 음악적 분석)

  • Kim, Mi-Sook
    • The Journal of the Korea Contents Association
    • /
    • v.22 no.4
    • /
    • pp.714-726
    • /
    • 2022
  • The purpose of this paper is to find out the way of utilizing phrases of Chinese poetry in Manjeongje and its musical characteristics. To this end, the roles of phrases contained in the Pansori words were classified into five patterns: landscape description, strengthening of pleasant emotions, strengthening of sad emotions, wordplay, and combination of various poems. As a result of analysis, phrases quoted in sad mood part consist of slow rhythm of Jinyangjo and Jungmori, and sad melody of Gyemyun-gil and Jingyemyun tone; thus, both the rhythm and melody are expressed in accordance with the mood of poems. On the other hand, the melody in the landscape description parts, and the rhythm in the joyful feeling and wordplay parts showed the characteristics of determining the mood. In addition, when applying the analysis results to the perspective of Pansori composition, it is necessary to discover novel texts, apply to editorials, and study musical implementation suitable for the original mood in order to create more artistic Pansori.

A Study on Fraud Detection in the C2C Used Trade Market Using Doc2vec

  • Lim, Do Hyun;Ahn, Hyunchul
    • Journal of the Korea Society of Computer and Information
    • /
    • v.27 no.3
    • /
    • pp.173-182
    • /
    • 2022
  • In this paper, we propose a machine learning model that can prevent fraudulent transactions in advance and interpret them using the XAI approach. For the experiment, we collected a real data set of 12,258 mobile phone sales posts from Joonggonara, a major domestic online C2C resale trading platform. Characteristics of the text corresponding to the post body were extracted using Doc2vec, dimensionality was reduced through PCA, and various derived variables were created based on previous research. To mitigate the data imbalance problem in the preprocessing stage, a complex sampling method that combines oversampling and undersampling was applied. Then, various machine learning models were built to detect fraudulent postings. As a result of the analysis, LightGBM showed the best performance compared to other machine learning models. And as a result of SHAP, if the price is unreasonably low compared to the market price and if there is no indication of the transaction area, there was a high probability that it was a fraudulent post. Also, high price, no safe transaction, the more the courier transaction, and the higher the ratio of 0 in the price also led to fraud.

A Study on the Change of Visitor's Perception with the Implementation of Korean Important Agricultural Heritage System: The Field Agricultural Area of the Volcanic Island in Ulleung (국가중요농업유산 제도 시행에 따른 방문객 인식 변화: 울릉 화산섬 밭농업 지역을 대상으로)

  • Do, Jeeyoon;Jeong, Myeongcheol
    • Journal of Environmental Impact Assessment
    • /
    • v.31 no.3
    • /
    • pp.173-183
    • /
    • 2022
  • The purpose of this study is to explore the purpose of introducing the system and the possibility of development by comparing the period before and after the implementation of the Korean Important Agricultural Heritage System (KIAHS) using big data. In terms of perception related to Ulleungdo Island, keywords related to accessibility were derived as higher keywords before and after designation, and in particular, keywords such as various approaches and new ports could be found after designation. It can be seen that positive perception increased after the designation of KIAHS, and the perception of good increased particularly. In addition, the exact name of wild greens and keywords for volcanic island appeared in common, but it was confirmed that the influence increased in the results of the centrality analysis after the designation. In other words, it was found that the designation of KIAHS was helpful in preserving traditional knowledge and developing traditional agricultural culture using it.

Object Detection Algorithm for Explaining Products to the Visually Impaired (시각장애인에게 상품을 안내하기 위한 객체 식별 알고리즘)

  • Park, Dong-Yeon;Lim, Soon-Bum
    • The Journal of the Korea Contents Association
    • /
    • v.22 no.10
    • /
    • pp.1-10
    • /
    • 2022
  • Visually impaired people have very difficulty using retail stores due to the absence of braille information on products and any other support system. In this paper, we propose a basic algorithm for a system that recognizes products in retail stores and explains them as a voice. First, the deep learning model detects hand objects and product objects in the input image. Then, it finds a product object that most overlapping hand object by comparing the coordinate information of each detected object. We determine that this is a product selected by the user, and the system read the nutritional information of the product as Text-To-Speech. As a result of the evaluation, we confirmed a high performance of the learning model. The proposed algorithm can be actively used to build a system that supports the use of retail stores for the visually impaired.

Critical Discourse Analysis on Drug Addiction (마약 중독에 대한 비판적 담론 분석)

  • Shin, Seon-Hee
    • The Journal of the Korea Contents Association
    • /
    • v.22 no.9
    • /
    • pp.712-726
    • /
    • 2022
  • The purpose of this study is to find out what discourse the newspaper's articles produce and distribute about 'drug addiction' and to reveal the topography and meaning of the discourse. Data were collected by searching 'drug' 'drug addiction' as keywords for news articles in four daily newspapers in Korea. As a result of analyzing using Norman Fairclough's critical discourse analysis, first, the 'crime-punishment' discourse was dominant in textual analysis. Drug addiction is a social evil and a serious crime such as sex crimes, child crimes, and violence, so it should be strictly punished. Second, in the discourse practice analysis, drug addiction is a mental disease that needs treatment, so systematic management by the state is required. Third, in the socio-cultural practice analysis, drug addiction is a means of making money for economic benefit, is related to corruption of political power, and is an object that should be strongly controlled to prevent drug crimes from threatening the foundation of the state. Culturally, drug addiction stems from the motivation of pleasure seeking, and is the result of moral degradation. Through this analysis, the conversion to the 'disease-treatment' discourse and drug policies centered on treatment and rehabilitation were suggested as alternatives.

A Text Mining Analysis on Students' Perceptions about Capstone Design: Case of Industrial & Management Engineering (텍스트 마이닝을 활용한 캡스톤 디자인에 관한 학생 인식 탐색: 산업경영공학 사례)

  • Wi, Gwang-Ho;Kim, Yun-jin;Kim, Moon-Soo
    • Journal of Engineering Education Research
    • /
    • v.25 no.5
    • /
    • pp.85-93
    • /
    • 2022
  • Capstone Design, a project-based learning technique, is the most important curriculum that clarifying major knowledge and cultivating the ability to apply through the process of solving problems in the industrial field centered on the student project team. Accordingly, various and extensive studies are being conducted for the successful implementation of capstone design courses. Unlike previous studies, this study aimed to quantitatively analyze the opinions that recorded the experiences and feelings of students who performed capstone design, and used text mining methodologies such as frequency analysis, correlation analysis, topic modeling, and sentiment analysis. As a result of examining the overall opinions of the latter period through frequency analysis and correlation analysis, there was a difference between the languages used by the students in the opinions according to gender and project results. Through topic modeling analysis, 'topic selection' and 'the relationship between team members' showed an increase in occupancy or high occupancy, and topics such as 'presentation', 'leadership', and 'feeling what they felt' showed a tendency to decreasing occupancy. Lastly, sentiment analysis has found that female students showed more neutral emotions than male students, and the passed group showed more negative emotions than the non-passed group and less neutral emotions. Based on these findings, students' practical recognition of the curriculum was considered and implications for the improvement of capstone design were presented.