한국농수산대학 졸업생 영농정착 성공 사례집의 Text Mining - 주요단어의 빈도 분석 및 word cloud -

주진수,김종숙,박석영,송천영,Joo, J.S.,Kim, J.S.,Park, S.Y.,Song, C.Y. 국립한국농수산대학교 교육개발센터 2018 현장농업연구지 = Journal of practical agricultural resear Vol.20 No.2

In order to extract meaningful information from the excellent farming settlement cases of young farmers published by KNCAF, we studied the key words with text mining and created a word cloud for visualization. First, in the text mining results for the entire sample, the words 'CEO', 'corporate executive', 'think', 'self', 'start', 'mind', and 'effort' are the words with high frequency among the top 50 core words. Their ability to think, judge and push ahead with themselves is a result of showing that they have ability of to be managers or managers. And it is a expression of how they manages to achieve their dream without giving up their dream. The high frequency of words such as "father" and "parent" is due to the high ratio of parents' cooperation and succession. Also 'KNCAF', 'university', 'graduation' and 'study' are the results of their high educational awareness, and 'organic farming' and 'eco-friendly' are the result of the interest in eco-friendly agriculture. In addition, words related to the 6th industry such as 'sales' and 'experience' represent their efforts to revitalize farming and fishing villages. Meanwhile, 'internet', 'blog', 'online', 'SNS', 'ICT', 'composite' and 'smart' were not included in the top 50. However, the fact that these words were extracted without omission shows that young farmers are increasingly interested in the scientificization and high-tech of agriculture and fisheries Next, as a result of grouping the top 50 key words by crop, the words 'facilities' in livestock, vegetables and aquatic crops, the words 'equipment' and 'machine' in food crops were extracted as main words. 'Eco-friendly' and 'organic' appeared in vegetable crops and food crops, and 'organic' appeared in fruit crops. The 'worm' of eco-friendly farming method appeared in the food crops, and the 'certification', which means excellent agricultural and marine products, appeared only in the fishery crops. 'Production', which is related to '6th industry', appeared in all crops, 'processing' and 'distribution' appeared in the fruit crops, and 'experience' appeared in the vegetable crops, food crops and fruit crops. To visualize the extracted words by text mining, we created a word cloud with the entire samples and each crop sample. As a result, we were able to judge the meaning of excellent practices, which are unstructured text, by character size.

类词缀“云”及“云X”词族研究

王卉 ( Wang Hui ),朴兴洙 ( Park Heungsoo ) 한국중국언어학회 2020 중국언어연구 Vol.0 No.89

In order to meet the reference of new things and new phenomena appearing in the society, people have to create some new words and use them to complete the communicative needs. As a linguistic phenomenon, “cloud X” has existed for a long time, and even stagnated because it only consists of words related to computer and network. However, with the spread of COVID-19 at the beginning of 2020, the quasi affix “cloud”seems to have been given new meaning, produced a new combination, and has become one of the most active quasi affixes at this stage. Therefore, this paper chooses the quasi affix “cloud” as the research object, analyzes and studies the “cloud” and “cloud” words from four aspects: the semantics of “cloud”, the quasi-affixation of “cloud”, the structural characteristics of “cloud X” and the formation and development mechanism of “cloud” family of words.

워드 클라우드에 의한 환대 경영 전략

노형남 ( Hyung Nam Noh ) 대한관광경영학회 2014 觀光硏究 Vol.29 No.4

본 연구에서는 상호작용하는 클라우드 컴퓨팅 모듈을 구현함으로써 각각의 개별적인 다중참여자 연결마디에 추가되는 과부하를 부담시키지 않으면서도 전체 증강현실(augmentedreality)에 영속성을 부여할 수 있도록 다중참여 증강현실이 강화된 응용소프트웨어를 수행할 경우 필요한 증강현실 모형 데이터베이스를 효율적으로 관리하여 자발적 다중참여자가 이에 쉽게 접속할 수 있는 사용자 직접생산 디지털 콘텐츠로서 능동적인 워드 클라우드에 의한 환대 경영 전략을 제안한다. 증강현실 참여자가 정보의 대부분을 시각을 통해 얻기 때문에 정보처리에 있어서 영상정보 처리가 가장 중요하기는 하지만 다중이 사용자가 직접 생산하는 디지털 콘텐츠로 참여하는 증강현실이 제고된 정보전달을 위해서는 다른 감각정보의 융합처리기술도 필요함을 피력한다. 본 연구에서 제안하는 개선방안에 따라 적절한 조치가 빅 데이터 텍스트 마이닝으로 채택된다면 실제현실에 거의 완벽할 정도로 가까운 첨단의 증강현실을 실감하는 정보 처리 기술을 선점할 뿐만 아니라 새로운 응용소프트웨어 개발을 통해 세계 시장에서 우리나라의 지역화를 지향하는 워드 클라우드에 의한 환대 경영 전략의 경쟁력 확보가 가능하다. 또한 체계적인 전문 인력 양성에 기여함으로써 클라우드 컴퓨팅 증강현실에서 환대산업 활성화는 물론이려니와 정보기술의 경쟁력을 도모할 수 있다. This study focuses on word cloud-driven hospitality management strategy in a tourist potential community. According to the analogous way this study figures out the most adequate word cloud concerning hospitality industries. Hopeful perspective of this study is affirmative to explain on-line voluntary word cloud-driven hospitality management strategy as a spoonfed hospitality industry based on warmhearted goodwill. To be in the van of the new era the above-mentioned word cloud-driven hospitality management strategy it would be advisable to spread out predominantly in the tourist potential community on the analogous way of rethinking about ultra modern information technology and voluntary communication in multi-disciplinary sciences destroying high barrier established among them during a long period of time, applying voluntary word cloud-driven hospitality management strategy analyzed by big data text mining using program R.

『源氏物語』においての美的語彙の役割

권익호(Kwon Ik-Ho),박혜자(Park Hye-Ja) 대한일어일문학회 2010 일어일문학 Vol.48 No.-

Japanese language is known for its rich aesthetic words. The Tale of Genji offers varied collection of aesthetic words which makes it one of the most important writings in Japanese ancient literature. Different words play different roles in people's perception of the theme when they read literature written in a specific language; aesthetic words should create an emotional state of mind. This study categorizes 105 aesthetic words from ancient Japanese literature into five groups to develop a tentative scale of emotion called G-scale. Then the G-scale is paired with another scale called E-scale designed to show the degree of emotionality of the themes of chapters in the Tale of Genji. 1,756 pairs of G-scale and E-scale are mapped on the XY-plot to create a "cloud-map" for each of five different groups of ancient Japanese aesthetic words. The result shows that chapters with high emotion (i.e. high E-scale) have higher frequencies for groups of aesthetic words with high emotionality (i.e. high G-scale). This suggests that aesthetic words in Japanese language play a certain significant role in people's perceiving the themes of literature.

A Big Data Analysis of A Hot Political Issue

강남길 한국중원언어학회 2024 언어학연구 Vol.- No.70

The ultimate goal of this paper is to analyze 22 newspaper articles written in December, 2023 regarding Justice Minister Han. This research was carried out by python. A point to note is that the word minister was the most widely used, followed by the word representative, the word politics, the name Han, Dong-hoon, and the word general election, in descending order. When it comes to the network analysis of the relevant data, the ministry of justice and the Minjoo party of Korea are deemed to be core words in 22 newspaper articles. Finally, we classified the relevant words such as nouns and verbs into the positive one or the negative one. We assigned +1 to the positive one, whereas we assigned –1 to the negative one. By doing so, we could produce reasonable results with respect to Justice Minister Han. Most importantly, we obtained 14 positive words, whereas we obtained 6 negative words. It is clear from our findings that the majority of newspapers think highly of Justice Minister Han.

비정형 데이터 마이닝을 활용한 한국농수산대학 재학생의 학교생활 감성 분석(1)

주진수,이소영,김종숙,송천영,신용광,박노복,Joo, J.S.,Lee, S.Y.,Kim, J.S.,Song, C.Y.,Shin, Y.K.,Park, N.B. 국립한국농수산대학교 교육개발센터 2019 현장농업연구지 = Journal of practical agricultural resear Vol.21 No.1

In this study we examined the preferences of eight college living factors for students at Korea National College of Agriculture and Fisheries(KNCAF). Analytical techniques of unstructured data used opinion mining and text mining techniques, and the analysis results of text mining were visualized as word cloud. The college life factors included eight topics that were closely related to students: 'my present', 'my 10 years later', 'friendship', 'college festival', 'student restaurant', 'college dormitory', 'KNCAF', and 'long-term field practice'. In the text submitted by the students, we have established a dictionary of positive words and negative words to evaluate the preference by classifying the emotions of positive and negative. As a result, KNCAF students showed more than 85% positive emotions about the theme of 'student restaurant' and 'friendship'. But students' positive feelings about 'long-term field practice' and 'college dormitory' showed the lowest satisfaction rate of not exceeding 60%. The rest of the topics showed satisfaction of 69.3~74.2%. The gender differences showed that the positive emotions of male students were high in the topics of 'my present', 'my 10 years later', 'friendship', 'college dormitory' and 'long-term field practice'. And those of female were high in 'college festival', 'student restaurant' and 'KNCAF'. In addition, using text mining technique, the main words of positive and negative words were extracted, and word cloud was created to visualize the results.

Korean Public Values Revealed in Portal News Rankings

Hyoungbin Park 한국공공가치학회 2021 공공가치연구 Vol.2 No.1

Purpose: In this study, I focused on the social and cultural characteristics of Korea and the moral characteristics of Koreans. Ultimately, I examined the characteristics of Korean moral culture. I tried to look at the internet news rankings to confirm the moral culture of Koreans. I tried to study the ranking of internet news by age to gauge what kind of consciousness and values Koreans have. Method: For this purpose, the titles up to the 5th in the gender ranking of DAUM portal news were analyzed by word cloud. The value-related terms that appeared in the articles viewed the portal ranking news with the most interest through big data word cloud analysis from July 20th to 24th, 2021. Results: First, I identified general conceptual definitions and characteristics of values, morals, and ethics. Second, I examined the value-related terms that appeared in the articles that viewed the portal ranking news with the most interest through big data word cloud analysis. Third, I inferred the characteristics of moral culture that appeared in the news of interest by age groups of Koreans used in this study. Fourth, I explored the meaning of these analysis results in terms of the moral education in Modern Korea. Conclusion: The interest in articles by age group is different. It can be inferred that women have relationship-oriented tendencies and men have collectivistic tendencies toward society and the state. However, there are several limitations in generalizing the gender differences analyzed based on this ranking news.

네트워크 기반 대한민국 역대 대통령 취임사 분석

김학용(Hak Yong Kim) 한국콘텐츠학회 2021 한국콘텐츠학회논문지 Vol.21 No.11

대통령 취임사는 국가 비전을 제시하고 대통령의 정치철학, 정책기조와 방향을 국민들에게 전달할 수 있는 매우 유용한 수단이다. 이런 이유로 취임사를 분석하는 것은 해당 대통령을 이해하고 그 시대를 파악하는데 도움을 줄 것이다. 대통령 취임사는 다양한 학문분야에서 분석할 수 있지만, 본 연구에서는 취임사를 하나의 콘텐츠로 보고 네트워크를 기반으로 분석하고자 하였다. 취임사에 등장하는 단어의 빈도수를 중심으로 분석하는 단어구름이 널리 사용되지만 네트워크를 기반으로 분석하면 문장 속에 들어있는 맥락을 도출할 수 있기 때문에 유용한 방법이 될 것이다. 대한민국 역대 대통령 취임사 전체 네트워크를 구축하고 구조인자를 제시하였다. 네트워크로부터 도출한 핵심단어 및 단어구름의 핵심단어를 비교분석하여 대통령의 정책 방향 등을 도출하였다. 대통령 각각의 취임사 네트워크를 구축하여 핵심단어 및 네트워크의 구조인자인 근접 중심성을 비교 분석하여 취임사의 특성을 제시하였다. 네트워크 기반 역대 대통령 취임사 분석은 궁극적으로 대통령의 이해와 평가를 위한 자료로 활용할 수 있을 것으로 기대한다. The presidential inaugural address is a very useful means of presenting the national vision and conveying the presidents political philosophy and policy direction to the people. For this reason, analyzing the address will help to understand the president him/herself and the presidential times. The address can be analyzed in various academic fields, but in this study, it was considered as only content and analyzed based on the network. It is widely used for word cloud analysis based on the frequency of words appearing in the address. If it is analyzed based on a network, it will be a useful method because it is possible to derive the context contained in the sentence. The entire network of the addresses of past presidents of the Republic of Korea was established and structural factors were presented. The president and political direction were derived by comparatively analyzing the key words derived from the network and the word cloud. The characteristics of the address were presented by comparing and analyzing key words and closeness centrality, which is a structural factor of the network, by constructing a network of each presidents inaugural address. It is expected that the network-based analysis of past presidential inaugural addresses can ultimately be used as data for understanding and evaluating presidents.

신문 빅데이터 기반의 언어 계량과 시각화

김일환 서강대학교 언어정보연구소 2019 언어와 정보 사회 Vol.38 No.-

This paper quantifies information on the frequency of use or distribution of language and examines methods and cases of visually illustrating its results. First, we discuss problems of large-scale language data related to the quantification of language information. Moreover, we look through several methods of quantifying language information and effectively visualizing its results. Through the Dong-A Ilbo newspaper corpus, we have proven that a rather simple linear graph can represent the change of word frequency effectively. Considering the change of frequency according to time, we adopt the statistical measure t-score. We calculate the key words and visualize its results via a word cloud. Also, we process network visualization using Pajek to extract co-occurring words that share contexts with particular words and spot their relevance. Finally, it is shown that a bar graph and multidimensional scaling can be properly utilized to compare the words’ frequency and visualize the similarity.

병원 홈페이지의 병원장 메시지를 통한 경영전략 분석: 텍스트 마이닝 기법을 활용하여

나형종,원다빈 세명대학교 인문사회과학연구소 2023 人文 社會科學硏究 Vol.31 No.2

· Research topic: This study presented meaningful information on hospital management using text mining techniques for hospital management information contained in the message of the hospital director, which is unstructured text data. · Research background: On most hospital websites, the hospital director mentions the vision or value of the hospital through messages. In this study, we focused on the hospital director's message among the data disclosed on the hospital website and tried to derive meaningful qualitative information on hospital management through text mining techniques on the vision, strategy, goals, and values of the hospital. · Differences from prior research: The differences between this paper and previous studies can be summarized as follows. First, this paper presented the research results so that hospitals can grasp their management strategies at a glance by extracting information on the vision or goals of hospital management through text data on the website. Second, in the field of strategic research, few studies have objectively analyzed CEO messages published on the website through text mining techniques. This paper provides more objectively useful information by analyzing texts from various angles using TF-IDF analysis, topic modeling analysis, network analysis, and word-to-back analysis among text mining techniques. · Research Method: The sample period of this study is as of December 31, 2022, and the sample target is 65 hospitals corresponding to general hospitals and university hospitals among hospitals in Korea. For this study, the hospital director's message posted on each hospital's website was crawled, and the analysis of the hospital director's text message, which is unstructured text data, used Rver 3.6.3, an open source data analysis tool. Specifically, TF-IDF analysis, topic modeling analysis, network analysis, and word-to-back analysis were used. · Research results: The summary of the research results of this paper is as follows. First, the results of the TF-IDF analysis are as follows. Words such as "hospital," "medical," "regional," "medical," "patient," "service," "center," "disease," "health," and "effort" were found to have high TF-IDF values. Second, the topic modeling results are as follows. The main keywords of Topic 1 are "health," "insurance," "environment," "harmony," "domyo," "creation," and "consideration," which can be inferred as "health and welfare-related topics." In addition, the main keywords of Topic 2 are derived from 'advanced', 'system', 'specialization', 'promotion', 'medicine', 'overseas', 'activation', and 'medical personnel', which can be inferred as 'topics related to advanced medical systems'. Finally, the main keywords of Topic 3 were derived as "residents," "nursing," "university hospitals," "free," "visit," "hold," "health checkups," and "neighbors," which can be inferred as "topics related to local residents support projects." Third, the keyword network analysis results are as follows. "Patient," "care," "region," "service," and "center" are words that mean "regional treatment centers," and keyword network analysis showed that they are related to each other. In addition, "hospital," "medical," "effort," "development," and "best" are words that mean "hospital effort and development," and the keyword network analysis found that they are interrelated. Fourth, the results of the correlation analysis between keywords using Word2Vec are as follows. Based on the results of topic modeling, the relevance was identified based on the words 'health welfare', 'advanced', and 'support'. Regarding "health welfare," it was found to be highly related in the order of "social welfare," "best," "improvement," "ebaji," "contribution," "people," "promotion," "health," "domyo," and "citizen." In addition, it was found that "advanced" was highly related in the order of "latest", "secured", "introduced", "excellent", "infrastructure", "implementation", "investment", "state... · 연구 주제: 본 연구는 비정형 텍스트 자료인 병원장의 메시지에 내포된 병원 경영정보에 대해서 텍스트 마이닝 기법을 활용하여 병원경영에 관한 의미 있는 정보를 제시하였다. · 연구 배경: 대부분의 병원 홈페이지에서는 병원장이 메시지를 통해 병원의 비전이나 가치 등에 대해서 언급하고 있다. 본 연구에서는 병원 홈페이지에서 공시하는 자료 중 병원장 메시지에 초점을 두고 병원의 비전, 전략, 목표, 가치 등에 대해서 텍스트 마이닝 기법을 통해 병원경영에 의미 있는 정성적 정보를 도출하고자 하였다. · 선행연구와의 차이점: 본 논문과 선행연구와 차이점은 다음과 같이 요약할 수 있다. 첫째, 본 논문은 병원경영의 비전이나 목표 등에 관한 정보를 홈페이지의 텍스트 자료를 통해 추출함으로써 병원들의 경영전략에 대해서 한 눈에 파악할 수 있도록 연구결과를 제시하였다. 둘째, 기존에 전략 연구 분야에서 홈페이지에 공시한 CEO 메시지를 텍스트마이닝 기법을 통해 객관적으로 분석한 연구는 거의 없었다. 본 논문에서는 텍스트 마이닝 기법 중 TF-IDF 분석, 토픽모델링 분석, 네트워크 분석, 그리고 워즈투백 분석을 사용하여 다양한 각도에서 텍스트들을 분석함으로써 보다 객관적으로 유용한 정보를 제공하였다. · 연구방법: 본 연구의 표본 기간은 2022년 12월 31일을 기준이며, 표본대상은 우리나라 병원 중 종합병원 및 대학병원에 해당하는 65개의 병원이다. 본 연구를 위해 각 병원 홈페이지에 게시된 병원장 메시지를 크롤링(crawling)하였고, 비정형 텍스트 데이터인 병원장 텍스트 메세지의 분석은 오픈 소스 데이터 분석 도구인 R ver 3.6.3을 활용하였다. 구체적으로 TF-IDF 분석, 토픽모델링 분석, 네트워크 분석, 그리고 워즈투백 분석을 사용하였다. · 연구결과: 본 논문의 연구결과를 요약하여 제시하면 다음과 같다. 첫째, TF-IDF 분석 결과는 다음과 같다. ‘병원’, ‘의료’, ‘지역’ ‘진료’, ‘환자’, ‘서비스’, ‘센터’, ‘질환’, ‘건강’, ‘노력’ 등의 단어들이 TF-IDF값이 높은 것으로 나타났다. 둘째, 토픽 모델링 결과는 다음과 같다. Topic 1의 주요 키워드가 ‘보건’, ‘보험’, ‘환경’, ‘화합’, ‘도모’, ‘조성’, ‘배려’ 등으로 나타난 것으로 보아 ‘보건 및 복지 관련 토픽’으로 유추할 수 있다. 그리고 Topic 2의 주요 키워드는 ‘첨단’, ‘시스템’, ‘전문화’, ‘추진’, ‘의학’, ‘해외’, ‘활성화’, ‘의료인’ 등으로 도출된 것으로 보아 ‘첨단 의학 시스템 관련 토픽’으로 유추할 수 있다. 마지막으로 Topic 3의 주요 키워드가 ‘주민’, ‘간호’, ‘대학병원’, ‘무료’, ‘방문’, ‘보유’, ‘건강검진’, ‘이웃’ 등으로 도출된 것으로 보아 ‘지역 주민 지원 사업 관련 토픽’으로 유추할 수 있다. 셋째, 키워드 네트워크 분석 결과는 다음과 같다. ‘환자', ‘진료', ‘지역', ‘서비스’, ‘센터’는 “지역별 진료 센터”를 의미하는 단어들로 키워드 네트워크 분석 결과 서로 연관성이 있는 것으로 나타났다. 그리고 ‘병원’, ‘의료’, ‘노력’, ‘발전’, ‘최고’는 “병원의 노력과 발전”을 의미하는 단어들로 키워드 네트워크 분석결과 상호 연관성이 있는 것으로 도출되었다. 넷째, Word2Vec을 이용한 키워드 간 연관성 분석결과는 다음과 같다. 토픽모델링 결과에 기반으로 하여 ‘보건복지’, ‘첨단’, ‘지원’이라는 단어를 기준 ...