• 제목/요약/키워드: words

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Pragmatics and Translation in the Use of English Words in Banner Advertising on Portal Sites

  • Ban, Hyun;Noh, Bo Kyung
    • International Journal of Advanced Culture Technology
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    • 제9권3호
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    • pp.259-264
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    • 2021
  • In modern socity, online communication plays a vital role in social interaction of communicities. It is so common for online users to see display advertisements online while surting the Net. Specifically, most web banners diaplayed on portral sites consist of words, phrase, and sentences. Considering that the primary purpose of adversiting is persuation, the advertisement such as web banners is an examplary case to show the interaction among pragmatics, translation and advertising because the linguistic expressions employed in the banners represent its pragmatic use, leading to persuation and functioning as a communicative tool for the smooth communication between source text producers (adversisers) and target audience (online users). This can be part of the so-called translation process. In particular, we can easily witness the use of English words in web banners. Thus, this paper looks at web banners displayed on major four portal sites-Naver, Daum, Nate, and Zum, giving a special attention to the content contained in the web banners as well as the use of English words. As s result, we found that the frequencies of English words in each portal site were higher when the advertised products were targeting young online users, whereas the frequencies were lower when the users are older group than young people. The finding supports the prgramatic perspective that linguistic expressions are understood in social contexts and shows the so-called translation process which involves a shift from semantic meaning of words to their pragmatic use. Finally, we can conclude that the interaction is possible when we have the framework where translation, pragmatics, and advertising are all communitative components for social interaction within social contexts.

Identification of Profane Words in Cyberbullying Incidents within Social Networks

  • Ali, Wan Noor Hamiza Wan;Mohd, Masnizah;Fauzi, Fariza
    • Journal of Information Science Theory and Practice
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    • 제9권1호
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    • pp.24-34
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    • 2021
  • The popularity of social networking sites (SNS) has facilitated communication between users. The usage of SNS helps users in their daily life in various ways such as sharing of opinions, keeping in touch with old friends, making new friends, and getting information. However, some users misuse SNS to belittle or hurt others using profanities, which is typical in cyberbullying incidents. Thus, in this study, we aim to identify profane words from the ASKfm corpus to analyze the profane word distribution across four different roles involved in cyberbullying based on lexicon dictionary. These four roles are: harasser, victim, bystander that assists the bully, and bystander that defends the victim. Evaluation in this study focused on occurrences of the profane word for each role from the corpus. The top 10 common words used in the corpus are also identified and represented in a graph. Results from the analysis show that these four roles used profane words in their conversation with different weightage and distribution, even though the profane words used are mostly similar. The harasser is the first ranked that used profane words in the conversation compared to other roles. The results can be further explored and considered as a potential feature in a cyberbullying detection model using a machine learning approach. Results in this work will contribute to formulate the suitable representation. It is also useful in modeling a cyberbullying detection model based on the identification of profane word distribution across different cyberbullying roles in social networks for future works.

Word2Vec를 이용한 토픽모델링의 확장 및 분석사례 (Expansion of Topic Modeling with Word2Vec and Case Analysis)

  • 윤상훈;김근형
    • 한국정보시스템학회지:정보시스템연구
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    • 제30권1호
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    • pp.45-64
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    • 2021
  • Purpose The traditional topic modeling technique makes it difficult to distinguish the semantic of topics because the key words assigned to each topic would be also assigned to other topics. This problem could become severe when the number of online reviews are small. In this paper, the extended model of topic modeling technique that can be used for analyzing a small amount of online reviews is proposed. Design/methodology/approach The extended model of being proposed in this paper is a form that combines the traditional topic modeling technique and the Word2Vec technique. The extended model only allocates main words to the extracted topics, but also generates discriminatory words between topics. In particular, Word2vec technique is applied in the process of extracting related words semantically for each discriminatory word. In the extended model, main words and discriminatory words with similar words semantically are used in the process of semantic classification and naming of extracted topics, so that the semantic classification and naming of topics can be more clearly performed. For case study, online reviews related with Udo in Tripadvisor web site were analyzed by applying the traditional topic modeling and the proposed extension model. In the process of semantic classification and naming of the extracted topics, the traditional topic modeling technique and the extended model were compared. Findings Since the extended model is a concept that utilizes additional information in the existing topic modeling information, it can be confirmed that it is more effective than the existing topic modeling in semantic division between topics and the process of assigning topic names.

기능적 조음음운장애 아동의 조음복잡성에 따른 자음과 단어의 음향학적 길이 (Acoustic Duration of Consonants and Words by Phonetic Complexity in Children with Functional Articulation and Phonological Disorders)

  • 강은영
    • 대한통합의학회지
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    • 제9권4호
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    • pp.167-181
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    • 2021
  • Purpose : This study was conducted to investigate whether phonetic complexity affected the type and frequency of articulation errors and the acoustic duration of consonants and words produced by children with functional articulation and phonological disorders. Methods : The participants in this study were 20 children with functional articulation and phonological disorders and 20 children without such disorders who were between 3 years 7 months old and 4 years 11 months old. The participants were asked to name what they saw in pictures and their responses were recorded. The types and frequencies of articulation errors and the acoustic duration of words were analyzed and words were categorized as being of either 'high' or 'low' phonetic complexity. The acoustic duration of initial and final consonants and vowels following initial consonants were compared between the groups according to articulatory complexity. Results : Children with functional articulation and phonological disorders produced articulation errors more frequently when saying high complexity words and had longer word duration when saying low-complexity words than children without such disorders. There was no major difference in initial and final consonant duration between the groups. but the main effect of articulatory complexity on the duration of both consonants was significant. Conclusion : These results suggest that the articulatory-phonic structure of words influences the speech motor control ability of children with functional articulation and phonological disorders. When articulating consonants, children with functional articulation and phonological disorders had speech motor control ability similar to that of children without such disorders.

딥러닝을 이용한 기형도 시의 핵심 이미지 분석 (Deep Learning Application for Core Image Analysis of the Poems by Ki Hyung-Do)

  • 고광호
    • 문화기술의 융합
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    • 제7권3호
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    • pp.591-598
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    • 2021
  • 전후방 단어들의 인접 여부 혹은 후방 단어들의 순서를 학습할 수 있는 통계 기법인 SVD, 딥러닝 기법인 CBOW, LSTM으로 단어벡터를 구할 수 있다. 이렇게 학습된 단어벡터를 기형도의 시에 적용하여 핵심 이미지를 대표하는 단어들과 유사도 높은 단어를 구해서 분석해 보았다. 시적 이미지와 어울리지 않는 단어들이 연산되기도 하지만 그 단어가 사용된 시적 맥락에서는 기준 단어와 유사한 이미지를 표현하고 있음을 알 수 있었다. 이러한 단어벡터를 활용하면 핵심 이미지를 대표하는 단어들의 관계와 유사한 관계의 다른 단어들도 유추할 수 있다. 따라서 통계 기법인 SVD 및 딥러닝 기법인 CBOW와 LSTM으로 구한 단어벡터의 유사도 및 유추 연산을 통해 대상 시를 다양하고 심도 깊게 분석할 수 있다.

Research Trends Analysis on ESG Using Unsupervised Learning

  • Woo-Ryeong YANG;Hoe-Chang YANG
    • 융합경영연구
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    • 제11권3호
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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.

빅 데이터를 활용한 레트로 패션과 뉴트로 패션에 대한 인식 비교 (Comparative Analysis in Perception of Retro Fashion and New-tro Fashion Using Big Data)

  • 백경자;김정미
    • 한국의상디자인학회지
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    • 제25권1호
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    • pp.83-96
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    • 2023
  • The purpose of this study is to compare and analyze the perception of retro fashion and new-tro fashion using big data. TEXTOM allowed the collection of big data on the words 'retro fashion' and 'new-tro fashion', which was refined afterwards. As for the data collection period, Jan. 1, 2019 to Nov. 30, 2022 was set. A top 50 list of words were extracted from this data based on appearance frequency. The extracted words were processed through Network centrality analysis and CONCOR analysis using Ucinet 6. The results are as follows. 1) In retro fashion, the appearance frequency of 'style' was the highest, followed by 'sensibility', 'color', 'trend', 'fashion', and 'brand'. These words came up with high TF-IDF values. Network centrality analysis discovered that 'color', 'style', 'trend', 'sensibility', and 'design' had high level of connectivity with other words. CONCOR analysis showed a total of four significant groups; trends, styles, looks, and photos. 2) In new-tro fashion, the appearance frequency of 'retro' was the highest, followed by 'trend', 'generation', 'style', 'brand', and 'fashion'. These words also came up with high TF-IDF values. Network centrality analysis found that 'retro', 'trend', 'generation', and 'brand' had high level of connectivity with other words. CONCOR analysis showed a total of four significant groups; style, brand, clothing, and trend. 3) New-tro fashion is included in retro fashion in that it reproduces the styles of the past. However, it is taken completely differently from generation to generation. Unlike the older generations, millennials actively accept newly created clothes and brands based on the past styles. They perceive it as a fashion that reveals their own unique tastes and tastes.

빅 데이터를 활용한 고프코어 룩에 대한 인식 (The Perception of Gorpcore Look Using Big Data)

  • 김지우;김정미
    • 한국의상디자인학회지
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    • 제25권4호
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    • pp.77-92
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    • 2023
  • The purpose of this study is to investigate the public perception of Gorpcore through Big Aata analytics. The study was conducted based on the collection of Big Data on the word 'Gorpcore' through Textom from July 24, 2017 to March 31, 2023. As a result, 63,386 words were collected from a total of 18,879 posts, and the top 50 words were determined based on frequency of appearance. Based on the collected words, centrality measures and CONCOR algorithm were performed in Ucinet 6. The research results are as follows. 1) The frequency of appearance was high in the order of 'Gorpcore look', 'fashion', 'coordination', 'clothes', 'outdoor', 'Musinsa', 'look', 'trend', 'brand' and 'ahjussi (middle-aged old man in Korean)'. These words had high TF-IDF scores, which leads to the conclusion that these are key words that are recognized as important. 2) Network centrality shows that 'Gorpcore look', 'fashion', 'outdoor', 'coordination', 'clothes', 'trend', 'look' and 'style' have a high correlation with other words. Through this, it was found that the public thinks it is important to create a variety of fashions by styling high-performance outdoor wear and casual wear, and that they are highly interested in clothes and in brands leading the Gorpcore trend. 3) As a result of the CONCOR algorithm, four significant groups were formed. The words that appear in each group are as follows. Group 1 - 'outdoor', 'Gorp', 'Normcore', 'hiking', 'functionality', 'new', 'sports', 'casual wear', 'activity', 'generation', 'collaboration'. Group 2 - 'fashion', 'trend', 'look', 'brand', 'style', 'shoes', 'ugly', 'item', 'trend', 'product', 'Salomon', 'padded jacket', 'stylishness', 'utilization', 'Winter', 'street', 'design', 'retro', 'popular', 'styling'. Group 3 - 'Gorpcore look', 'coordination', 'Musinsa', 'windbreaker', 'recommendation', 'Arcteryx', 'pants', 'man'. Group 4 - 'clothes' 'ahjussi', 'jacket', 'launching', 'spring', 'The North Face', 'collection', 'utility', 'jumper'. As a result, it can be seen that the Gorpcore is also regarded as a part of outdoor, fashion, coordination, and casual wear.

학위논문의 주요어 분석 (간호학 및 간호학관련 학위논문을 중심으로 : 1960-1991. 8) (A Statistical Study on the Key Words in the Titles of Nursing Related Theses)

  • 고옥자;김상혜;김희걸;이금재;이영숙
    • 대한간호학회지
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    • 제24권1호
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    • pp.58-69
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    • 1994
  • In order to see the development of Nursing related research activities in Korea over the last three decades, abstracts of almost all of the Master and Ph.D theses that appeared from 1961 up to August 1991 were collected. The number of theses was 2354, from which an index of key words has been constructed. Key words were defined as those terms in each thesis title that convey major objectives of the given thesis study and the important nursing concepts dealt with in the thesis. Although all the key words were picked from the thesis title only, full use was made of the abstracts in deciding the principal objectives and essential contents of the thesis studies and their important concepts as well. In total, 539 kinds of key words were identified from the 2354 titles, and the identified words were all found to be in the International Nursing Index. On an average each title has two key words. Which key words were most frequently used, how they have changed with time, what kind of concept is preferably dealt with by each graduate school, and the concepts to which a given key word is likely to be connected were examined. The results are summerized below : 1) For each decade the theses numbers were as follows : 54(2.3%) from the 60’s, 413(17.5%) from the 70’s, 1523(64.7%) from the 80’s, and 364(15.5%) from the 90’s. Master’s thesis contributed 96% (2252) of the papers and Ph. D’s theses filled the remaining 4%(102). 2) A total of 539 key words were used, averaging about 2 for each thesis. The most frequently used key words were ‘Nurse’, ‘Anxiety’, ‘Knowledge / Attitude /Practice’, ‘Stress /Stressor’, ‘Attitude’, ‘Job-Satisfaction’, ‘Mental Disorder’, ‘Operation’, ‘Elderly’, ‘Nursing Role’. 3) Each decades key words can be classified as : the 60’s : ‘Nursing Education’, ‘Pulmonary Tuberculosis’, ‘Mother-Child Health’, ‘Growth & Development’, ‘Public Facilities’, ‘Mental Disorder’ : the 70’s : ‘Nurse’, ‘Family Planning’, ‘Attitude’ / ‘Knowledge, Attitude / Practice’, ‘Curriculum in Nursing Education’, ‘Clinical Practice in Nursing’, ‘Analysis of the Work of the Nurse’, ‘Health Education of School’, : the 80’s : ‘Nurse’, ‘Anxiety’, ‘Stress /Stressor’, ‘Operation’, ‘Nursing Role’, ‘Job Satisfaction’ : the 90’s : ‘Nurse’, ‘Elderly’, ‘Family-Support’, ‘Stress /Stressor’, ‘Home Care’. Key word ‘Nurse’ appears continuously and most frequently through the years, which indicates that there has been active study of the characteristics of nurses and related fields. The concept ‘Anxiety’ has been studied steadly from the 80’s and it shows that interest in health and disease are increasing Which comes as a result of society changing to an industrial and informational community. 4) Looking into each graduate school’s study area key words ‘Anxiety’, ‘Nurse’, ‘Mental Disorder’, ‘Stress /Stressor’, ‘Operation’, ‘Attitude’, ‘Hemo-dialysis’, were studied in the regular graduate school : ‘Family Planning /Contraception’, ‘Knowledge / Attitude /Practice’, ‘Physical Health-State /Physical Health Examination’, ‘Nurse’, ‘Using Clinical Facilities’, ‘Health Education of School’, were studied in the Graduate School of Public Health’ ; ‘Nurse’, ‘Anxiety’, ‘Stress / Stressor’, ‘Job-Satisfaction’, ‘Clinical Practice Education’, ‘Nursing Education’, were studied in the Graduate School of Education : ‘Nurse’, ‘Job Satisfaction’, ‘Nursing Role’, ‘Administration - Employment /Employment Management’, ‘Leadership’, ‘Personnel Profile’, ‘Nursing Manpower / Changing Working Place’, were studied in the Graduate School of Public Administration. 5) The Connection between key words were : ‘Nurse Job Satisfaction’, ‘Stress / Stressor ⇔ Coping / Ajustment’, ‘Nurse ⇔ Nursing Role’, ‘Anxiety ⇔ Giving Information’, ‘Nurse ⇔ Stress / Stressor’, ‘Anxiety ⇔ Operation’, ‘Nurse ⇔ Burnout’, ‘Knowledge, Attitude, Practice ⇔ Family Planning’, ‘Nurse Administration ⇔ Employment’, ‘Anxiety Muscle ⇔ Relaxation Technic’, ‘Anxiety ⇔ Mental Disorder’. From the above it can be noted that many nursing concepts were handled in the thesis titles. But there were more than enough papers on the characteristics of the nurse. It is suggested that in depth research be made on ‘Nursing Accidents’, t-‘Ethics’, ‘Nurse - Patient Interactions’, ‘Spritual Care’, ‘Dying’, ‘Hospice’, ‘Resident Helper’ and that there should be in depth research relating to the physical and mental development of youth and in particular physical concepts like ‘Drug - Abuse’, ‘Child -Abuse and Teaching’.

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k-Structure를 이용한 한국어 상품평 단어 자동 추출 방법 (Automatic Extraction of Opinion Words from Korean Product Reviews Using the k-Structure)

  • 강한훈;유성준;한동일
    • 한국정보과학회논문지:소프트웨어및응용
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    • 제37권6호
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    • pp.470-479
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    • 2010
  • 감정어 추출과 관련하여 기존 영어권 연구에서 제시된 방법의 대부분은 한국어에 직접 적용이 쉽지 않다. 한국어권 연구에서 제시된 방법 중 수작업에 의한 방법은 감정어 추출에 많은 시간이 걸린다는 문제점이 있다. 영어 시소러스 기반 한국어 감정어 추출 기술은 한국어와 영어 단어간 일대일 부정합에서부터 기인하는 정확도의 저하를 제고해야 하는 과제를 갖고 있다. 한국어 구문 분석기를 기반으로 한 연구는 출현 빈도가 낮은 감정어를 선정하지 못할 수 있는 문제점을 내포하고 있다. 본 논문에서는 한국어 상품평 중 단순한 문장에서 감정어를 자동으로 추출하는 데 있어 기존에 제안된 한국어권 연구에 상호 보완적으로 정확도를 향상시킬 수 있는 k-Structure(k=5 또는 8) 기법을 제안한다. 단순한 문장이라 함은 패턴 길이를 최대 3으로 한다. 이는 평가 대상 상품(예를 들어 '카메라')의 속성 명 f (예를 들어 카메라의 '배터리')를 기준으로 ${\pm}2$의 거리에 감정어가 포함되어 있는 문장을 의미한다. 성능 실험은 국내 주요 쇼핑몰로부터 수집한 1,868개의 상품평을 대상으로 미리 주어진 8개의 속성 명에 대한 감정어를 k-Structure를 이용하여 자동으로 추출하고 그 정확도를 평가하였다. 그 결과, k=5일 경우 평균 79.0%의 재현률, 87.0%의 정확률을 보였고, k=8일 경우 평균 92.35%의 재현률, 89.3%의 정확률을 얻을 수 있었다. 또한, 영어권 연구에서 제안된 방법 중 PMI-IR(Pointwise Mutual Information-Information Retrieval) 기법을 이용하여 실험을 수행하였다. 이 결과, 평균 55%의 재현률과 57%의 정확률을 보였다.