• Title/Summary/Keyword: word frequency analysis

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Disfluency in Language Development (언어발달 과정에 나타난 비유창성 연구)

  • Kim, Tae-Kyung;Chang, Kyung-Hee
    • MALSORI
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    • no.67
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    • pp.61-77
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    • 2008
  • The purpose of this study is to blow the characteristics of disfluency in childhood. The subjects were 144 normal children at the age of between 3 to 8 years who lived in Seoul. All the subjects provided spontaneous conversational speech samples during free-play interactions with their friends. We investigated the patterns and the frequency of disfluency and its relevance with subject's age, speaking rate and MLU(mean length of utterance). The results of this study can be summarized as follows. (1) There was no difference in the frequency of disfluency with the speaker's age or speaking rate. (2) Interjection was the most frequently occurring pattern of disfluency. (3) Prolongation, revision, interjection increased with age while part-word repetition, single-syllable word repetition, multi-syllable word repetition decreased gradually. (4) A significant effect of MLU on the frequency of disfluencies were demonstrated. The regression analysis has shown that more disfluencies occurred in utterances of children whose MLU is longer.

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Text Mining of Wood Science Research Published in Korean and Japanese Journals

  • Eun-Suk JANG
    • Journal of the Korean Wood Science and Technology
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    • v.51 no.6
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    • pp.458-469
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    • 2023
  • Text mining techniques provide valuable insights into research information across various fields. In this study, text mining was used to identify research trends in wood science from 2012 to 2022, with a focus on representative journals published in Korea and Japan. Abstracts from Journal of the Korean Wood Science and Technology (JKWST, 785 articles) and Journal of Wood Science (JWS, 812 articles) obtained from the SCOPUS database were analyzed in terms of the word frequency (specifically, term frequency-inverse document frequency) and co-occurrence network analysis. Both journals showed a significant occurrence of words related to the physical and mechanical properties of wood. Furthermore, words related to wood species native to each country and their respective timber industries frequently appeared in both journals. CLT was a common keyword in engineering wood materials in Korea and Japan. In addition, the keywords "MDF," "MUF," and "GFRP" were ranked in the top 50 in Korea. Research on wood anatomy was inferred to be more active in Japan than in Korea. Co-occurrence network analysis showed that words related to the physical and structural characteristics of wood were organically related to wood materials.

A Study on the Research Trends in Domestic/International Information Science Articles by Co-word Analysis (동시출현단어 분석을 통한 국내외 정보학 학회지 연구동향 파악)

  • Kim, Ha Jin;Song, Min
    • Journal of the Korean Society for information Management
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    • v.31 no.1
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    • pp.99-118
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    • 2014
  • This paper carried out co-word analysis of noun and noun phrase using text-mining technique in order to grasp the research trends on domestic and international information science articles. It was conducted based on collected titles and articles of the papers published in the Journal of the Korean Society for Information Management (KOSIM) and Journal of American Society for Information Science and Technology (JASIST) from 1990 to 2013. By dividing whole period into five publication window, this paper was organized into the following processes: 1) analysis of high frequency co-word pair to examine the overall trends of both information science articles 2) analysis of each word appearing with high frequency keyword to grasp the detailed subject 3) focused network analysis of trend after 2010 when distinctively new keyword appeared. The result of the analysis shows that KOSIM has considerable portion of studies conducted regarding topics such as library, information service, information user and information organization. Whereas, JASIST has focused on studies regarding information retrieval, information user, web information, and bibliometrics.

The Effects of Beauty Service on Customer Satisfaction and Word-of-Mouth Intention in the Beauty Industry (머리미용서비스가 고객만족과 구전의도에 미치는 영향)

  • Park, Eun-Jung
    • Journal of the Korean Society of Clothing and Textiles
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    • v.31 no.4 s.163
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    • pp.574-583
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    • 2007
  • This study aimed to look into the features of the hair beauty service components and the effects of these elements on customer satisfaction and word-of-mouth intention. Subjects were 20's-40's women and survey methods such as frequency analysis, t-test, ANOVA, factor analysis, reliability analysis, and regression analysis were used. Results were as follows: First, hair beauty service were composed of eight factors such as facilities of hair beauty salon, employee's kindness, amusement facilities, light refreshments, guidance to a process of hair style, keeping service for personal belongings, reservation service, and customer management. Second, the effects on customer satisfaction was significantly affected by facilities of hair beauty salon, employee's kindness, guidance to a process of hair style, customer management, keeping service for personal belongings, light refreshments. Third, customer satisfaction with hair beauty service affected the word-of-mouth intention.

The Effect of Brand Loyalty and Word of Mouth between Trust and Commitment of Silver Women and Salesperson (실버여성과 화장품 판매원과의 신뢰와 관계몰입이 브랜드 충성도 및 구전효과에 미치는 영향)

  • Park, Sung-Hee;Hong, Byung-Sook
    • Journal of the Korean Society of Clothing and Textiles
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    • v.31 no.7
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    • pp.1139-1147
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    • 2007
  • Word of mouth is becoming increasingly in the market these days as company offers many product, advertising, promotion for consumer. The Purpose of this study is to the effect of brand loyalty and word of mouth between trust and commitment of silver women and salesperson. A survey was conducted from October 15 to September 10 in 2006, among over the 60 aged silver women. 260 silver women subjects were frequency analysis, reliability analysis, factor analysis, multiple regression analysis. The results are as follows: First, a degree of trust factors were determined to be specialty, benevolence, And a degree of commitment factors were determined to be calculative commitment, effective commitment. Second, a degree of trust and commitment factors had an effect on brand loyalty. Third, brand loyalty effect on word of mouth. The research finds that trust and commitment of multidimensional view effect on word of mouth and moderating effect of relationship.

Effects of the Service Quality and Information Quality of ChatGPT on Purchase Intention and Word of Mouth Intention for Fashion Products (챗GPT의 서비스 품질과 정보 품질이 패션 제품의 구매의도와 구전의도에 미치는 영향)

  • Hyeonhye Park;Yoonsun Lee;Eunjeong Shin
    • Journal of the Korean Society of Clothing and Textiles
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    • v.47 no.6
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    • pp.1038-1056
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    • 2023
  • This study investigates the effects of ChatGPT's quality characteristics (service and information) on purchase intention and word of mouth intention. We distributed questionnaires among domestic men and women aged in their 20s and 30s who had experience of using ChatGPT. A total of 222 responses were subjected to frequency analysis, factor analysis, correlation analysis, and multiple linear regression analysis using the IBM SPSS statistical program version 26. The major findings were as follows: (1) The factors of service quality were categorized as Tangibility, Reliability, Empathy, and Assurance, while the factors of information quality were categorized as Recency, Accuracy, and Usefulness. (2) Among the service quality factors of ChatGPT, two factors (Reliability and Empathy) significantly impacted purchase intention, and three factors (Tangibility, Reliability, and Empathy) significantly affected word of mouth intention. (3) Among ChatGPT's information quality factors, two factors (Usefulness and Recency) had a significant effect on purchase intention, and two factors (Usefulness and Accuracy) exerted a significant influence on word of mouth intention. (4) Purchase intention had a significant effect on word of mouth intention.

A Study on the Product Planning Model based on Word2Vec using On-offline Comment Analysis: Focused on the Noiseless Vertical Mouse User (온·오프라인 댓글 분석이 활용된 Word2Vec 기반 상품기획 모델연구: 버티컬 무소음마우스 사용자를 중심으로)

  • Ahn, Yeong-Hwi
    • Journal of Digital Convergence
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    • v.19 no.10
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    • pp.221-227
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    • 2021
  • In this paper, we conducted word-to-word similarity analysis of standardized datasets collected through web crawling for 10,000 Vertical Noise Mouses using Word2Vec, and made 92 students of computer engineering use the products presented for 5 days, and conducted self-report questionnaire analysis. The questionnaire analysis was conducted by collecting the words in the form of a narrative form and presenting and selecting the top 50 words extracted from the word frequency analysis and the word similarity analysis. As a result of analyzing the similarity of e-commerce user's product review, pain (.985) and design (.963) were analyzed as the advantages of click keywords, and the disadvantages were vertical (.985) and adaptation (.948). In the descriptive frequency analysis, the most frequently selected items were Vertical (123) and Pain (118). Vertical (83) and Pain (75) were selected for the advantages of selecting the long/demerit similar words, and adaptation (89) and buttons (72) were selected for the disadvantages. Therefore, it is expected that decision makers and product planners of medium and small enterprises can be used as important data for decision making when the method applied in this study is reflected as a new product development process and a review strategy of existing products.

Exploration of Research Trends in The Journal of Distribution Science Using Keyword Analysis

  • YANG, Woo-Ryeong
    • The Journal of Industrial Distribution & Business
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    • v.10 no.8
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    • pp.17-24
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    • 2019
  • Purpose - The purpose of this study is to find out research directions for distribution and fusion and complex field to many domestic and foreign researchers carrying out related academic research by confirming research trends in the Journal of Distribution Science (JDS). Research Design, Data, and Methodology - To do this, I used keywords from a total of 904 papers published in the JDS excluding 19 papers that were not presented with keywords among 923. The analysis utilized word clouding, topic modeling, and weighted frequency analysis using the R program. Results - As a result of word clouding analysis, customer satisfaction was the most utilized keyword. Topic modeling results were divided into ten topics such as distribution channels, communication, supply chain, brand, business, customer, comparative study, performance, KODISA journal, and trade. It is confirmed that only the service quality part is increased in the weighted frequency analysis result of applying to the year group. Conclusion - The results of this study confirm that the JDS has developed into various convergence and integration researches from the past studies limited to the field of distribution. However, JDS's identity is based on distribution. Therefore, it is also necessary to establish identity continuously through special editions of fields related to distribution.

Research Trends Analysis on ESG Using Unsupervised Learning

  • Woo-Ryeong YANG;Hoe-Chang YANG
    • The Journal of Economics, Marketing and Management
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    • v.11 no.3
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    • pp.47-66
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    • 2023
  • Purpose: The purpose of this study is to identify research trends related to ESG by domestic and overseas researchers so far, and to present research directions and clues for the possibility of applying ESG to Korean companies in the future and ESG practice through comparison of derived topics. Research design, data and methodology: In this study, as of October 20, 2022, after searching for the keyword 'ESG' in 'scienceON', 341 domestic papers with English abstracts and 1,173 overseas papers were extracted. For analysis, word frequency analysis, word co-occurrence frequency analysis, BERTopic, LDA, and OLS regression analysis were performed to confirm trends for each topic using Python 3.7. Results: As a result of word frequency analysis, It was found that words such as management, company, performance, and value were commonly used in both domestic and overseas papers. In domestic papers, words such as activity and responsibility, and in overseas papers, words such as sustainability, impact, and development were included in the top 20 words. As a result of analyzing the co-occurrence frequency of words, it was confirmed that domestic papers were related mainly to words such as company, management, and activity, and overseas papers were related to words such as investment, sustainability, and performance. As a result of topic modeling, 3 topics such as named ESG from the corporate perspective were derived for domestic papers, and a total of 7 topics such as named sustainable investment for overseas papers were derived. As a result of the annual trend analysis, each topic did not show a relatively increasing or decreasing tendency, confirming that all topics were neutral. Conclusions: The results of this study confirmed that although it is desirable that domestic papers have recently started research on consumers, the subject diversity is lower than that of overseas papers. Therefore, it is suggested that future research needs to approach various topics such as forecasting future risks related to ESG and corporate evaluation methods.

A Study on Multi-frequency Keyword Visualization based on Co-occurrence (다중빈도 키워드 가시화에 관한 연구)

  • Lee, HyunChang;Shin, SeongYoon
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2018.05a
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    • pp.103-104
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    • 2018
  • Recently, interest in data analysis has increased as the importance of big data becomes more important. Particularly, as social media data and academic research communities become more active and important, analysis becomes more important. In this study, co-word analysis was conducted through altmetrics articles collected from 2012 to 2017. In this way, the co-occurrence network map is derived from the keyword and the emphasized keyword is extracted.

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