Earticle

본 논문은 ‘공공(임대)주택’에 대한 경기도의회 의원들의 입장을 분석한다. 경기도의회(3 대, 1991년)부터 10대(2021년)까지 경기도의회 홈페이지에 등재된 30년의 ‘속기(회의)록 (Text-Big data)’을 대상으로 정당별로 그리고 선수별로 의원 발언을 분류하고 ‘공공(임대) 주택’에 대한 의원 발언이 긍정적인지 부정적인지를 분석하여 발언의 추이와 의원의 입장 차이를 밝힌다. 연구 방법은 빅데이터 분석에 적합한 텍스트마이닝(Text-Mining)을 위해 R 을 사용하여 단어 정제와 빈도 분석을 실시하였다. 또한 발언 내용을 긍정과 부정의 관점 에서 분석하기 위해 내용 분석을 실시하였다. 분석 결과 경기도의회 속기(회의)록에서 '주 택'과 관련한 발언 중 '공공(임대)주택' 발언이 차지하는 비중은 22%로 나타났다. 1. 정당별, 진보와 보수 간의 발언 빈도의 격차는 시기별 역전 현상에도 불구하고 ‘공공(임대)주택’은 보수와 진보 모두 90% 이상 ‘긍정적’인 내용의 발언으로 이루어져 있는 것으로 분석 되었 고 2. 초선 및 재선 이상의 의원들의 ‘공공(임대)주택’에 대한 긍정적인 발언은 90%(52명, 101회)로 의원들 대부분이 긍정적 입장을 나타내었다.

Housing continues to be a social issue, and one of the most important policies to be addressed by central and local governments. As we approach the 30th anniversary of local self-government, it is necessary to examine the position of local councils in the debate over public (rental) housing. However, there are only a few previous studies in this regard, and they are limited to analyzing local governments (such as Seoul Metropolitan Government) rather than local councils. This paper analyzes the stance of members of the Gyeonggi Provincial Assembly on 'public (rental) housing'. Using 30 years of 'shorthand (meeting) logs' (Text-Big data) listed on the Gyeonggi Provincial Assembly website from the 3rd (1991) to the 10th (2021), we classify lawmakers' remarks by party and player, and analyze whether their remarks on 'public (rental) housing' are positive or negative to reveal the trend of remarks and differences in lawmakers' positions. The research method utilized R, a text-mining tool suitable for big data analysis, to analyze the frequency of remarks, and the researcher read and organized the content of the secondary remarks. As a result of the analysis, the proportion of 'public (rental) housing' remarks among remarks related to 'housing' in the shorthand (meeting) record of the Gyeonggi Provincial Assembly was 22%. 1.Despite the disparity in the frequency of remarks between political parties and between liberals and conservatives, the position on 'public (rental) housing' was analyzed as consisting of more than 90% of 'positive' remarks by both conservatives and liberals. 2.The positive remarks on 'public (rental) housing' by first-time and re-elected legislators were 90% (52, 101 times), indicating that most of the legislators expressed a positive position.

본 연구는 질병과 관련한 온라인 포럼에서 추출한 언어 데이터를 통해 제 2형 당뇨병 환자의 질병에 대한 담론을 양적으로 분석하였다. 또한 환자 언어행위의 양적분석을 통해 환자들의 주요 관심사와 심리적 특징의 일반화가 가능한지에 대해 실증적으로 검증하였다. 분석방법으로는 기존의 인터뷰에 기반한 정성적 연구방법론과 달리 환자들의 담론 표본 전체를 파싱 (parsing)과 POS 태깅을 통해 언어학적으로 형태소 분류를 하였다. 주요 어휘빈도 추출과 N-gram을 통한 최빈도 구문구조 분석을 병행하여, 질병과 관련한 이슈의 주요 범주와 심리상태에 관한 언어적인 특징을 살펴보았다. 연구 결과 환자들의 자발적 대화는 주로 다이어트, 운동, 증상, 약물치료, 심리상태의 5가지 범주로 나타나고 있음을 확인하였고, 최빈도 구문구조 분석을 통해 질병치료와 식생활습관 개선 전반에 대한 부정적인 견해가 두드러진 것을 확인하였다. 결과적으로 의료진의 정확한 정보 전달과 전문가의 조언, 정서적 지원 등이 당뇨환자에 대한 심리적 상태에 중요한 만큼 심리치료 서비스이 개선이 필요할 것으로 보인다. 이런한 결과는 기존의 의료제도 안에서의 환자의 관심사와 심리적 특징이 온라인 상에서도 적절하게 투영되고 있음을 시사한다.

This paper has identified five major categories of the T2D patients’ concerns based on an online forum where the patients voluntarily verbalized their naturally occurring emotional reactions and concerns related to T2D. We have emphasized the fact that the lexical and phrasal analysis brought to the forefront the prevailing negative reactions and desires for clear information, professional advice, and emotional support. This study used lexical and phrasal analysis based on text-mining tools to estimate the potential of using a large sample of patient conversation of a specific disease posted on the internet for clinical features and patients’ emotions. As a result, the study showed that quantitative analysis based on text-mining is a viable method of generalizing the psychological concerns and features of T2D patients.

산업진흥 정책의 하나로 정보보호 인력양성 및 교육이 꾸준히 이루어지고 있지만, 시장에는 여전히 중고급 이상의 숙련인력은 부족하다. 정보보안 공시제도의 시행 및 확대에 따라, 정보보호를 전담할 전문인력의 확보 및 유지의 필요성은 더욱 커지고 있다. 하지만, 지능정보사회로의 진입에 따라 정보기술 업무와 정보보호 업무 간의 구분은 더욱 애매해지고 있어, 정보보호만의 전문성을 키우고 인정받기 위한 수단이 필요하다. 본 논문에서는 업무수행에 필요한 지식 및 기술을 규명하여 정보보호 전문성 확보를 위한 수단으로 활용하는 방안을 제안하고자 하였다. 2014년, 2019년, 2022년 게시된 정보보호 인력 구인광고 데이터를 수집하여, 직무 키워드를 비교한 결과, 구축, 운영, 기술지원, 네트워크, 보안솔루션 등이 주요 키워드임을 확인하였으며, 이는 년도별로 차이가 없었다. 또한, 기업의 실제 수요를 파악하기 위해, 텍스트마이닝 기법을 이용하여 구인광고 내용과 국가직무능력표준 정보보호 분야 지식기술 내용을 비교 분석하였다. 그 결과, 실제 현업에서는 기술개발, 네트워크, 운영체제 등 기술적인 능력을 선호하는 것으로 나타났지만, 직업훈련에서는 법제도, 인증제도 등 관리 능력이 우선시되고 있음을 확인하였다.

As a sufficient workforce supports the industry's growth, workforce training has also been carried out as part of the industry promotion policy. However, the market still has a shortage of skilled mid-level workers. The information security disclosure requires organizations to secure personnel responsible for information security work. Still, the division between information technology work and job areas is unclear, and the pay is not high for responsibility. This paper compares job keywords in advertisements for the information security workforce for 2014, 2019, and 2022. There is no difference in the keywords describing the job duties of information security personnel in the three years, such as implementation, operation, technical support, network, and security solution. To identify the actual needs of companies, we also analyzed and compared the contents of job advertisements posted on online recruitment sites with information security sector knowledge and skills defined by the National Competence Standards used for comprehensive vocational training. It was found that technical skills such as technology development, network, and operating system are preferred in the actual workplace. In contrast, managerial skills such as the legal system and certification systems are prioritized in vocational training.

본 연구 목적은 최근 세 정부의 스포츠정책 변화 추이를 문화체육관광부 장관 취임사를 통해 종합적으로 비교 분석하기 위한 것이다. 이를 위하여 문화체육관광부 홈페이지 및 포털사이트 네이버에서 문화체육관광부 장관 취임사 를 수집한 후 분석대상으로 선정하였다. 빅데이터 솔루션 프로그램인 텍스톰(Textom)을 통해 빈도 및 메트릭스 데이 터를 추출하고 UCINET6의 넷드로(NetDraw)기능을 이용하여 스포츠 및 체육과 관련된 단어들 사이의 네트워크를 시각화하였다. 본 연구결과는 다음과 같다. 첫째, 이명박 정부는 체육, 우리, 선진화, 체육인, 국민, 문화에서 스포츠정책 과 관련한 높은 중심성 키워드로 나타났다. 둘째, 박근혜 정부는 국민, 체육, 엘리트체육, 노력에서 스포츠정책과 관련한 높은 중심성 키워드로 나타났다. 셋째, 문재인 정부는 국민, 체육, 문화, 엘리트체육, 어린이, 선진화에서 스포츠정책과 관련한 높은 중심성 키워드로 나타났다. 결론적으로 최근 세 정부는 체육과 문화가 중요한 스포츠정책의 핵심어로 나타 났으며 특히, 국민의 스포츠 참여를 유도하고 경기력 향상 및 스포츠문화의 경쟁력을 강화하기 위한 중심의 정책이 수행 되고 있다. 따라서 정책을 통한 스포츠선진화를 이루기 위해서는 스포츠정책을 다변화 할 수 있는 정책개발과 그에 따른 지원 확대가 필요하다.

This study compares the recent changes in sports policy of the three governments with the inaugural speech of the Minister of Culture, Sports and Tourism. For this purpose, the inaugural address of the Minister of Culture, Sports and Tourism was collected on the web-site of the Ministry of Culture, Sports and Tourism and portal site Naver and selected as an analysis target. The big data solution program Textom extracted frequency and metric data and visualized the network between words related to sports and physical education using UCINET6's NetDraw function. The study results are as follows : First, Lee Myung-bak government, physical education, we, advancement, sportsman, people, culture appeared high center of keywords related to policy. Second, Park Geun-hye, the government, people, physical education, elite sports, efforts related to sports policy in a keyword in the center. Third, Moon Jae-in, the government, people, culture, physical education, culture, elite sports, children and advancement sports policy high keyword in the center. In conclusion, sports and culture have recently emerged as the key words for sports policy, and in particular, a central policy is being carried out to induce the people to participate in sports, improve their performance and enhance the competitiveness of sports culture. Therefore, in order to achieve the advancement of sports through policy, it is necessary to develop policies that can diversify sports policies and thus expand support accordingly.

한국의 저출산 심화에 따라 본 연구는 정부의 저출산 대응정책과 그에 대한 대중인식을 비교하여 근본적인 차이 점을 밝히고자 했다. 이를 위해 네 차례의 ‘저출산·고령사회 기본계획’과 제3·4차 기본계획 발표 직후 2주간의 뉴스 댓글을 분석대상으로 선정하여, 빈도분석, 동시출현단어 분석, 구조적 등위성 분석을 실시하였다. 정책문서 빈도분석 결과 제1·2차 시기는 직접적인 보육지원이, 제3·4차 시기부터는 사회구조적인 접근이 눈에 띄었다. 동시출현단어 분석 에서는 정책과 댓글 모두 ‘육아’에서 일과 가정의 양립을 지향하였다. ‘결혼’과 ‘출산’의 경우 댓글은 연속성, 정책은 단절성이 두드러지며 특히 주거와 고용문제에서 큰 차이가 있었다. 댓글의 구조적 등위성 분석 결과에서는 대중들의 자녀 양육환경에 대한 관심, 정책 실효성에 대한 문제의식을 확인할 수 있었다. 본 연구는 빅데이터를 활용해 대중들의 인식을 확인하였다는 점에서 의의를 가지므로, 이에 근거한 정책 개선 등 향후 저출산 대응이 나아가야 할 방향을 수립 하는 데 도움을 줄 수 있을 것이다.

As the low fertility intensifies in Korea, this study investigated fundamental differences between the government’s low fertility policy and public perception of it. To this end, we selected four times ‘Aging Society and Population Policy’ documents and news comments for two weeks immediately after announcement of the third and fourth Policy as analysis targets. Then we conducted word frequency analysis, co-occurrence analysis and CONCOR analysis. As a result of analyses, first, direct childcare support during the first and second periods, and a social structural approach during third and fourth periods were noticeable. Second, it was revealed that both policies and comments aim for the work-family compatibility in ‘parenting’. Lastly it was showed public interest in environment of raising children and the critical mind to effectiveness of the policy. This study is meaningful in that it confirmed the public perception using big data analysis, and it will help improve the direction for the future low fertility policy.

본 연구는 온라인 기업 리뷰 데이터를 활용하여 HR 관련 구성원 지각과 기업 성과 간의 연관성을 탐색적으로 분석하고, 리뷰 데이터 활용 가능성을 검토하고자 한다. Glassdoor 리뷰 데이터를 수집한 후 BERT 기반 감성 분석과 회귀 분석을 수행하였다. 분석 결과, 일부 HR 관련 요인은 기업 성과와 유의한 관계를 보이는 것으로 나타났다. 이는 기업 리뷰 데이터가 HR 제도에 대한 구성원 인식을 파악하는 보완적 자료원으로 활용될 수 있음을 시사한다. 다만 본 연구는 2020년 데이터를 활용한 탐색적 연구이므로, 분석 결과는 인과적 효과라기보다 온라인 리뷰에 나타난 HR 관련 지각과 기업 성과 간의 연관성으로 해석할 필요가 있다. 향후 다양한 데이터 통합과 장기적 분석을 통해 보다 정교한 HR 평가가 필요하다.

This study explores the relationship between employee perceptions of HR-related factors in online company reviews and firm performance, while examining the potential use of review data in HR research. Glassdoor reviews were collected and analyzed using BERT-based sentiment analysis and regression analysis. The results indicate that several HR-related factors are significantly associated with firm performance. These findings suggest that employee review data can serve as a supplementary source for capturing employees' perceptions of HR practices. However, because this study uses 2020 review data and adopts an exploratory design, the results should be interpreted as associations rather than causal effects. Future research should incorporate diverse data sources and longitudinal analyses to enable more refined HR evaluation.

본 연구는 최근 10년 동안(2009-2018) 국내 학술지에 발표된 감정노동(emotional labor) 관련 892편의 논문을 텍스트 마이닝(text-mining) 및 네트워크 분석(network analysis)을 활용하여 연구동향을 파악하는 것이 목적이다. 이를 위해 이들 논문의 주제어를 수집 및 코딩하여 최종적으로 871개의 노드(node)와 2625개의 링크 (link)로 변환시켜 네트워크 텍스트로 분석하였다. 첫째, 네트워크 텍스트 분석 결과로 동시출현빈도에 따른 상 위 4개 주요 주제어는 번아웃, 이직의도, 직무스트레스, 직무만족 순으로 나타났으며, 연결중심성에 따른 상위 4 개 주제어들의 빈도와 연결중심성 모두 비교적 높은 것으로 확인되었다. 둘째, 연결중심성 상위 4개의 주제어를 바탕으로 자아(ego)연결망 분석을 실시하여 각 네트워크의 연결중심도에 대한 주제어를 제시하였다.

The purpose of this study was to identify research trends of 892 domestic articles (2009-2018) related to emotional labor by using text-mining and network analysis. To this end, the keyword of these papers were collected and coded and eventually converted to 871 nodes and 2625 links for network text analysis. First, network text analysis revealed that the top four main keyword, according to co-occurrence frequency, were burnout, turnover intention, job stress, and job satisfaction in order and that the frequency and the top four core keyword by degree centrality were all relatively the high. Second, based on the top four core keyword of degree centrality the ego network analysis was conducted and the keyword for connection centroid of each network were presented.

Purpose: This study aimed to identify the main keywords, network structures, and topical themes in patient safety incident reports using text network analysis. Methods: The study analyzed patient safety incident reports from a general hospital in Seoul, covering a total of 3,576 cases reported over five years, from 2019 to 2023. Unstructured data were extracted from the text of the incident reports, detailing how the patient safety incidents occurred and how they were managed according to the six-part principles. The analysis was conducted in four steps: 1) word extraction and refinement, 2) keyword extraction and word network generation, 3) network connectivity and centrality analysis, and 4) topic modeling analysis. The NetMiner program was used for data analysis. Results: The analysis of degree, betweenness, and closeness centrality revealed that the most common keywords among the top five were "confirmation," "medication," "inpatient room," "caregiver," and "condition." Topic modeling analysis identified three main topic groups: 1) incidents caused by a lack of awareness of fall risk, 2) incidents of non-compliance with basic medication principles, and 3) incidents due to inaccurate patient identification. Conclusion: To prevent patient safety incidents, it is necessary to promote a culture of safety in hospitals, standardize patient identification procedures, and provide basic training in medication safety and fall prevention to healthcare staff. Furthermore, empirical research on patient safety practices is necessary to encourage active participation in patient safety activities by patients and family caregivers.

Purpose: The purpose of this study was to identify the supportive care needs of parents of preterm children in South Korea using text data from a portal site. Methods: In total, 628 online newspaper articles and 1,966 social network service posts published between January 1 and December 31, 2019 were analyzed. The procedures in this study were conducted in the following order: keyword selection, data collection, morpheme analysis, keyword analysis, and topic modeling. Results: The term "yirundung-yi", which is a native Korean word referring to premature infants, was confirmed to be a useful term for parents. The following four topics were identified as the supportive care needs of parents of preterm children: 1) a vague fear of caring for a baby upon imminent neonatal intensive care unit discharge, 2) real-world difficulties encountered while caring for preterm children, 3) concerns about growth and development problems, and 4) anxiety about possible complications. Conclusion: Supportive care interventions for parents of preterm children should include general parenting methods for babies. A team composed of multidisciplinary experts must support the individual growth and development of preterm children and manage the complications of prematurity using highly accessible media.

CrossRef is an association of scholarly publishers that develops shared infrastructure to support more effective scholarly communications. It is a registration agency for the digital object identifier (DOI), and has built additional services for CrossRef members around the DOI and the bibliographic metadata that publishers deposit in order to register DOIs for their publications. Among these services are CrossCheck, powered by iThenticate, which helps publishers screen for plagiarism in submitted manuscripts and FundRef, which gives publishers standard way to report funding sources for published scholarly research. To add to these services, Cross-Ref launched CrossRef text and data mining services in May 2014. This article will explain the thinking behind CrossRef launching this new service, what it offers to publishers and researchers alike, how publishers can participate in it, and the uptake of the service so far.

COVID-19로 인해 국내외 조직들은 전례없는 상황을 겪고 있으며 이에 대응하기 위한 리더십 연구 역시 부족한 실정이다. 본 연구는 COVID-19 전과 후의 리더십을 데이터로 규명하고자 했다. 이를 위해 한국 기업 조직에서 COVID-19 전과 후로 위기에 요구되는 리더십 행동 차이를 데이터 마이닝 방법을 통해서 규명했다. COVID-19가 팬데믹(Pandamic) 수준으로 선포 되기 이전에 구성원들은 리더들이 내재적/외재적 보상에 더욱 공을 들이고 수평적 조직문화를 만들어주기를 기대한 반면, COVID-19 시대에는 심리적 안전감, 잦은 소통, 미래에 대한 방향성 제시 등을 요구하고 있었다. 이와 같은 위기 상황에서 부각되는 리더십을 본 연구자들은 변혁적 리더십으로 간주하고 두 번째 연구를 설계하여 구성원들의 태도변수인 회복 탄력성과 관계를 실증했다. 회복 탄력성은 위기 상황에서 구성원들이 갖춰야 할 요소로 자주 언급된다. 변혁적 리더십이 COVID-19 시대에 도 회복 탄력성에 유의미하게 영향을 미치는지 살펴봤다. 분석 결과, 변혁적 리더십은 회복 탄력성과 정(+)의 관계를 가지고, 정서적 몰입은 변혁적 리더십과 회복 탄력성의 관계를 부분적으로 매개하였다. 본 연구는 COVID-19 이후로 요구되는 위기 리더십을 데이터로 규명했다는데 실무적으로 기여점을 가지고 있다. 더불어, 위기 상황에서 종종 강조되는 구성원 태도인 회복 탄력성과 관련성을 실증했다는 이론적인 기여점이 있다.

Many organizations are under crisis due to the pandemic of COVID-19, and they may need to understand different leadership during the crisis. This study consisted of two phases. In the first phase, leadership required after COVID-19 was studied by topical modeling which is one of data mining techniques. In the second phase, the primary purpose was to study the correlation between perceived leadership behaviors and personal performance through empirical analysis. Specifically, we analyzed the change in perceived leadership demanded by members of an organization by comparing before and after the declaration of COVID-19. Prior to the declaration, the members frequently mentioned leadership behaviors related to intrinsic and external rewards. After the declaration, on the other hand, words and phrases related to psychological safety, effective communication, and clear direction to the future were frequently observed. Based on the results of the first study, we determined the transformational leadership as the kind of leadership demanded during a crisis like COVID-19, and the second study was designed to test the relationship between perceived transformational leadership and the individual resilience among the members of the organization. In addition, we hypothesized that affective commitment mediates the relationship between the two variables, and the mediation was tested. As a result, we observed a positive relationship between the perceived transformational leadership and the individual resilience, and it was evident that affective commitment partially mediates the relationship. This research contributes to reveal the leadership behaviors demanded in the crisis of COVID-19 by the data mining technique which is important in HR practices. In addition, this research has a theoretical contribution by investigating the leadership style demanded during the time of a crisis and by relating to the individual attitudes. finally, limitations of this research and directions of future research are discussed.

Ik-seon dong is one of the hot place in Seoul especially in these days. This means lots of money and people have been gathering in Ik-seon dong, gentrification was resulted in here. This showed Seoul’s these day’s gentrification, Too fast. Actually Seoul wanted to make detailed design plan in Ik-seon dong, but because of rapid speed, it was really hard work. As a result the plan was made in 2018, but the gentrification of Ik-seon dong give lots of information. In this situation, for analysing the gentrification, proper information, such as land use, the number of visitors, would be needed. However it is really difficult work because there isn’t data base about that. Text-mining is a analysis method using social network, so in this research, there are proper opportunity to reveal Ik-seon dong’s Gentrification.

도덕적인 인간과 정의로운 시민은 도덕과 교육이 지향하는 인간상이 다. 도덕과 교육의 목표로서 두 인간상은 도덕성과 시민성, 도덕교육과 시민교육에 대한 논의의 연속선 상에 있다. 본 연구는 이러한 문제의 식을 바탕으로 도덕적인 인간과 정의로운 시민에 대한 한국 청소년의 인식을 확인하기 위해 진행되었다. 전국의 중·고등학생 942명을 대상 으로, 두 인간상에 대한 학생들의 서술을 텍스트 마이닝 기법을 활용하여 분석하였다. 연구결과에 따르면, 첫째, 두 인간상에 대한 학생들 의 인식은 상당 부분 중첩되어 있었다. 둘째, 도덕적인 인간을 정의하 는 방식에 있어 중학생들은 덕목을 중심으로 서술한 반면, 고등학생들 은 윤리에 대한 심화된 이해를 중심으로 서술하였다. 셋째, 정의로운 시민을 정의하는 방식은 학교 급의 변화에 따라 더 구체적이고 세부적 으로 나타났다. 연구결과를 바탕으로, 본 연구는 도덕과 교육과 도덕과 시민교육을 위한 몇 가지 제안을 한다.

A moral person and a just citizen are the desirable human character of moral education. This study aims to analyze the perception of a moral person and a just citizen. Korean youth's responses to two human characters were analyzed using the text-mining method. According to research, there was an overlapping domain between a moral person and a just citizen. In addition, middle school students described a moral person based on virtues, whereas high school students used the deeper terms of ethics. Finally, the detailed perceptions of a just citizen increased with age. On that basis, this study discusses moral and citizen education.

As technology becomes integral to customer experiences, the study investigates the adoption of technologies in hotels and their influence on traditional service. The integration of IoT is explored for its potential to create new experiences and increase customer satisfaction, alongside challenges such as security concerns and high investment costs. Therefore, this research gathered Google News data using the keywords "Smart Hotel" and "Hotel IoT" to analyze emerging trends in the hospitality sector. Co-occurrence network analysis and Latent Dirichlet Allocation (LDA) topic modeling unveil key clusters and topics, emphasizing customer experience, technology amenities, and intelligent operation. The findings contribute valuable insights into the evolving landscape of smart hotels and the relationship between IoT and the hospitality sector.

Culture was an always “overloaded” concept during Korea’s colonial period. Like the ideas of literature and art, it was one of the main routes through which Koreans developed a socio-political sense when they were forbidden to speak about politics. Starting in the 1920s especially, Koreans used culture to establish intellectual foundations of modernity, cultivate the masses’ aesthetic senses, and seriously engage with colonial reality. Furthermore, the idea of culture became more complicated in the late 1930s as the colonial government more aggressively employed the cultural idea to propagate a series of wars while mainlining Japan’s ascendency in East Asia. Reflecting upon such a conceptual tug of war by different socio-political actors, this article uses text-mining to explore the changing meanings of culture in a 1930s popular magazine. Run by the proponents of culture as a forefront of social movements, Samch’ŏlli (“Threethousand ri,” which figuratively refers to Korea) was a monthly magazine that lasted for more than a decade from 1929 to 1941, unlike many short-lived journals under censorship. By examining the frequency of the keywords that composed the theme of culture, and the semantic network of culture’s cooccurring words, we diachronically trace the polyphonic meanings of culture in different timeframes. These quantitative and linguistic methods suggest that culture’s semantic network drawn from a 1930s periodical was far larger, more diverse in composition, and more influential than explained in previous studies, especially in its interplay with the various socio-political actors in launching collective projects by Korean intellectuals and the colonial government.

The Environmental, Social, and Governance (ESG) metric is currently the gold standard for assessing how large corporations perform in these three areas of their daily operations. Despite the effectiveness of ESG in analyzing large corporations, little attention has been paid to micro-level research. Investment proposals that include ESG concepts are becoming more common, with major platforms encouraging entrepreneurs to consider these issues in their pitches. As a result, the conventional wisdom regarding these proposals is that the majority of them will result in a higher success rate due to the ESG trend. We investigate whether this is true by analyzing a Kickstarter dataset containing over 9000 online entrepreneurial pitches. To determine which characteristics of these entrepreneurial proposals resulted in increased investment, we used Ordinary Least Squares (OLS) and Logistic Regression. Contrary to popular belief, our findings revealed that using ESG themes in micro-entrepreneurial pitches increased the likelihood of failure..

With the development of deep learning techniques, text mining is producing breakthrough performance improvements, promising future applications, and practical use cases across many fields. Likewise, even though several attempts have been made in the field of financial information, few cases apply the current technological trends. Recently, companies and government agencies have attempted to conduct research and apply text mining in the field of financial information. First, in this study, we investigate various works using text mining to show what studies have been conducted in the financial sector. Second, to broaden the view of financial application, we provide a description of several text mining techniques that can be used in the field of financial information and summarize various paradigms in which these technologies can be applied. Third, we also provide practical cases for applying the latest text mining techniques in the field of financial information to provide more tangible guidance for those who will use text mining techniques in finance. Lastly, we propose potential future research topics in the field of financial information and present the research methods and utilization plans. This study can motivate researchers studying financial issues to use text mining techniques to gain new insights and improve their work from the rich information hidden in text data.

Recently, demand on application or using Bigdata analytics for CRM (Customer Relationship Management) has emerged in industry and academic research. However, most of previous text analytics studies validated algorithms and reported results of analysis without theoretical background or standardized framework. According to this reasons, expanding studies on various contexts and utilization have been limited. This study aims to develop theory-based framework on text mining techniques to evaluate service quality. Hence, previous studies and business cases are reviewed for selecting appropriate algorithms for measuring service quality. In this process, developed framework was applied to analysis customer’s online reviews. This study will be useful initial guideline on business operators who want to evaluate their service quality from user-generated-contents. It also has values on introductory business research on applied text data analysis and expand research scope and method on service research.

본 연구의 목적은 텍스트 마이닝을 활용하여 특허와 뉴스 기사 분석을 통해 블록체인 기술 동향을 탐색하고 사회적 관심을 파악하여 블록체인 정책의제를 제안하는 것이다. 이를 위해 국내 블록체인 특허 요약문 327건과 온라인 뉴스기사 전문 5,941건을 수집하고 전처리 과정을 거쳐 LDA 토픽모델링 방법을 사용하여 특허 토픽 12개와 뉴스 토 픽 19개를 추출하였다. 특허 분석을 통해 인증과 거래 관련 토픽이 높은 비중을 차지하였다. 뉴스 기사 분석 결과, 사회적 관심은 암호화폐에 치중되어 있는 것으로 나타났다. 이러한 분석 결과와 의제설정이론에 근거하여 블록체인 관련 정책의제를 도출하였다. 본 연구는 대용량 텍스트 문서 분석의 자동화된 기법을 활용하여 분석을 효율적·객관적으 로 수행하였으며, 블록체인 기술 동향과 사회적 관심도를 파악한 실증된 기초 분석 자료를 기반으로 정책의제를 제안하 였다. 본 연구에서 제시된 정책의제는 향후 정책 결정과정에의 기초자료로 활용될 수 있을 것이다.

The purpose of this study is to explore the trend of blockchain technology through analysis of patents and news articles using text mining, and to suggest the blockchain policy agenda by grasping social interests. For this purpose, 327 blockchain-related patent abstracts in Korea and 5,941 full-text online news articles were collected and preprocessed. 12 patent topics and 19 news topics were extracted with latent dirichlet allocation topic modeling. Analysis of patents showed that topics related to authentication and transaction accounted were largely predominant. Analysis of news articles showed that social interests are mainly concerned with cryptocurrency. Policy agendas were then derived for blockchain development. This study demonstrates the efficient and objective use of an automated technique for the analysis of large text documents. Additionally, specific policy agendas are proposed in this study which can inform future policy-making processes.