Earticle

Purpose: The aim of this study was to examine the behavioral responses of pregnant women during the early stage of Coronavirus Disease 2019 (COVID-19) outbreak. Methods: We recruited 1,099 women to complete an online questionnaire survey from February 10 to February 25, 2020. The subjects were divided into two groups (the pregnant women group and the control group). Results: Concerns about infection: most of the participants watched the COVID-19 news at least once a day. Protective behaviors: the utilization rate of pregnant women (often using various measures) was higher than that of nonpregnant women. Exercise: 30.6% of the pregnant women continued to exercise at home, whereas in the control group, this percentage was 8.4%. Spouse relationship: 38.8% of the subjects’ relationship improved, whereas only 2.3% thought the relationship was getting worse. Conclusion: Pregnant women had some unique behavioral responses different from that of nonpregnant women. It is important to understand the behavioral responses of pregnant women in this network era.

At present, lack of teaching effectiveness has become a serious problem in college, especially in the public mathematics courses. This paper attempts to study the effectiveness of mathematics classroom teaching through the network survey, as the Internet becomes popular media, Internet survey will become a mainstream form of investigation. The results show that teachers are more inclined to lecture style and question type teaching in mathematics course, while students prefer to explore cooperative learning mode. At the same time, 28% students never participate in course interaction, and 22% students only participate in course interaction which he thinks important. So that, how to mobilize the enthusiasm of the students is the main factor to improve the efficiency of classroom teaching. Generally speaking, effective teaching is comprehensive, dynamic and comprehensive, it should not only let the students get the basic knowledge, but also teach them the corresponding learning methods.

Network survey is a new kind of social investigation method, which is developed with the development of network technology, especially in the field of Social Science. In this paper, the author analyzes the performance of body language teaching in physical education by using network data, the result shows that students’ attention, confidence and energy has increased in body language teaching. At the same time, by comparing the control group and the experimental group data, we find that movement proficiency of experience group students has increased more significant. The total score of experience group is 86.10 5.24, while control group is 80.03 6.33. Also, we find that the classroom atmosphere is active in the experimental group, students showed active response, high emotion, thinking more sensitive and focused attention. So that, effective use of Body language teaching will have a positive influence in physical education

The development of the Internet has brought great opportunities for the sales of sports goods, so that enterprises should make the right online marketing strategy. This paper takes the consumer perception as the research content, study on the influence of different brand positioning factors on consumers by using empirical analysis. The results show that the factors affecting of brand can be divided into four categories as quality, product, service and social attributes. Among them, the quality is the most significant and the cumulative contribution rate is 79.532. Based on factor analysis method, the author identifies the main advantages and disadvantages of these brands, thus companies can effectively formulate the corresponding brand marketing strategy.

This study explores the differences of narcissistic customer financial investment in the bank's risk propensity and decision-making satisfaction. Studies have shown that overt narcissism customers have the higher degree of risk propensity. Investment professionals in overt narcissism and risk propensity between positive regulation effect is obvious, and overt narcissism and the degree of satisfaction with decision making is related; covert narcissism customer and risk propensity and decision-making satisfaction relationship is not significant and investment professionals in covert narcissism and risk propensity among regulatory role is not obvious. Covert narcissism and overt narcissism tendency and differences in risk decision satisfaction provide new ideas for the design and marketing of financial products.

Background: The Leicester Cough Questionnaire (LCQ) is a validated instrument for evaluating cough-related impairments within three domains: physical, psychological, and social. This study investigated how the physical, psychological, and social domains of chronic cough are interrelated using the LCQ. Methods: Adult patients with chronic cough from 16 respiratory centers who completed the LCQ and underwent diagnostic workup were retrospectively reviewed. Spearman's rank correlation was used to examine the correlations among LCQ items across the physical, psychological, and social domains. Causal mediation analysis was performed to partition the total effect between domains into direct and indirect effects mediated by the third domain. The mediation analysis findings were subsequently validated in an independent cohort. Results: Network analysis of LCQ items identified distinct patterns for each domain. Items in the physical domain showed weaker correlations both within and between domains compared to the psychological and social domains. In contrast, items in the psychological and social domains exhibited strong interrelationships. Mediation analysis demonstrated that direct effects from one domain to another differed among the three domains. The overall estimated effects of the physical domain on the social and psychological domains were largely mediated by the psychological (76.1%) and social domains (67.1%), respectively. Conversely, the mediating effect of the physical domain on the psychological and social domains was minimal, accounting for only 12.8% and 18.0%, respectively. Conclusion: Given the strong correlations and impact of the psychological and social domains, it is recommended that a thorough evaluation including psychosocial factors be incorporated into the management of chronic cough.

Social Networking Service (SNS) is prevailing rapidly in Japan in recent years. The most popular ones are Facebook, mixi, and Twitter, which are utilized in various fields of life together with the convenient tool such as smart-phone. In this work, a questionnaire investigation is carried out in order to clarify the current usage condition, issues and desired functions. More than 1,000 samples are gathered. Bayesian network is utilized for this analysis. After conducting the sensitivity analysis, useful results are obtained. Differences in usage objectives and SNS sites are made clear by the attributes and preference of SNS users. They can be utilized effectively for marketing by clarifying the target customer through the sensitivity analysis.

This paper investigates a probabilistic causation problem that causes increase the probabilities of their effects on a suitable probabilistic model. A Bayesian network is used to analyze causal relationships of questions in Korean alcoholism questionnaire survey. We made a Korean obsessive compulsive drinking scale questionnaire for college students, and collected 73 responses to 21 questions over the course of an interview with investigating personnel from three different groups of responders. To identify and justify the casual relationships among questions we built an intial Bayesian network with an expert point of view’s network structure. However, G-test analysis of the variables, survey questions, with sample data revealed several discrepancies from the initial Bayesian network regarding relationship between nodes and also introduced an isolated subgraph. Interestingly, 3 potential arcs were identified and used to construct a modified Bayesian network which best correspond to the intention of the alcoholism questionnaire. Future works will assess the significance of these potential arcs with larger data sets and investigate whether revision of the alcoholism questionnaire is necessary for better diagnosis.

세계정의프로젝트(WJP) 법치주의 지수는 세계 각국의 일반 대중 및 전문가들의 경험과 인식에 대한 설문조사를 바탕으로 개별 국가의 법치주의 수준을 측정한 것이다. WJP 법치주의 지수는 한국법제연구원의 국민법의식 조사연구에서 그 설문문항을 참조하기도 하였고, 국제투명성기구의 세계 각국 부패인식지수 산정 시 근거가 되는 원천자료이기도 하다. 본 논문에서는 이러한 WJP 설문문항의 중요성을 감안하여 2019년 일반인 설문조사에 사용된 설문문항을 대상으로 분석을 시도하였다. 우선 WJP 설문문항의 기반이 된 WJP 법치주의 지수의 개념 및 요소에 대해서 알아보고, WJP 설문문항의 설계 과정 및 설문 유형의 특징을 살펴보았다. 그리고 비정형 텍스트 데이터에 해당하는 WJP 설문문항에 텍스트 연결망 분석 기법을 적용하여 그를 분석해 보았다. 분석 결과는 워드 클라우드와 단어 간 연결망, 토픽 모델링으로 제시하였다. 이러한 분석 시도는 WJP 설문문항의 설계 의도와 응답자의 설문문항의 실제 이해를 객관적이고 정량적인 측면에서 분석해 보기 위한 것이었다.

The World Justice Project(WJP) Rule of Law Index measures the level of rule of law in individual countries based on surveys of the experiences and perceptions of the general public and experts around the world. The WJP Rule of Law Index was referred to in the survey by the Korea Legislation Research Institute in its study on Korean people’s legal consciousness, and is also the main source material used by Transparency International to calculate Corruption Perceptions Index around the world. In this paper, in consideration of the importance of these WJP questionnaires, I attempted to analyze the questionnaire used in the General Population Poll 2019. First, I reviewed the concepts and factors of the WJP Rule of Law Index based on the WJP questionnaire, and looked into the design process and survey type features of the WJP questionnaire. In addition, I analyzed the WJP questionnaire questions corresponding to unstructured text data by using text network analysis. The analysis results were presented as word cloud, word- to-word network and topic modeling. This analysis attempt was to examine the WJP's design intention of the questionnaire and the actual understanding of the questionnaire questions by respondents in an objective and quantitative aspect.

목적 이 연구의 목적은 대학 서술형 강의평가의 감정분석과 의미연결망 분석을 통해 수업 개선 방향과 시사점을 도출하는 것이다. 방법 분석자료는 A대학교 2020학년도 1학기부터 2023학년도 1학기까지의 서술형 강의평가 데이터 243,900건이며 감정단어를 긍정, 부정, 중립 순으로 분류하여 연도별, 과목별, 단과대학별 서술형 강의평가 내용의 빈도와 비율을 분석하였다. 텍스톰을 통해 N-gram, 클러스팅 분석을 하였고 Ucinet 6을 사용하여 키워드 간의 네트워크 중심성 분석과 시각화를 하였다. 결과 첫째, 연도별, 이수과목별, 단과대학별 서술형 강의평가 문항의 감정분석 추이는 모두 긍정적인 의견이 우세하게 나타났다. 둘째, 강의평가 내용의 키워드 빈도와 N-gram의 분석 결과, 긍정형 평가에서는 ‘수업’과 ‘감사’가, 부정형 서술형 강의평가에서는 ‘수업’, ‘과제’, ‘아쉽다’ 등의 빈도가 높았으며, ‘수업’은 ‘내용’, ‘진행’, ‘시간’, ‘아쉽다’라는 키워드를 중심으로 확장되었다. 셋째, 강의평가 내용의 키워드 간 의미연결망 분석 결과는 긍정형에서는 ‘감사’, ‘수업’, ‘수고’, ‘설명’, ‘학생’, ‘친절’, ‘도움’, ‘이해’, ‘과제’, ‘시간’ 등이 가장 많이 연결되는 중요한 키워드였다. 부정형 강의평가에서는 ‘수업’, ‘강의’, ‘교수’, ‘과제’, ‘아쉽다’, ‘어렵다’, ‘힘들다’, ‘시험’이 포함된 키워드가 가장 많은 연결로 분석되었다. 결론 본 연구는 서술형 강의평가 감정분석과 의미연결망 분석을 통해 수업 개선 방향을 제시할 수 있는 가능성을 보여주었다.

Objectives The purpose of this study was to derive directions and implications for quality of education through sentiment analysis and semantic network analysis of university descriptive course evaluations. Methods The analysis data consisted of 243,900 descriptive lecture evaluations from the first semester of 2020 to the first semester of 2023 at University A. Emotion words were classified in the order of positive, negative, and neutral, and the frequency and ratio of descriptive lecture evaluation contents by year, subject, and college were calculated. N-gram and clustering were analyzed using Textome, and network centrality between keywords was analyzed and visualized using Ucinet 6. Results First, in the sentiment analysis trend for descriptive lecture evaluation questions by year, course completed, and university, positive opinions were found to be dominant. Second, as a result of the keyword frequency and N-gram analysis of the lecture evaluation contents, the frequency of ‘class’ and ‘thank you’ was high in positive evaluations, and the frequency of ‘class’, ‘assignment’, and ‘unsatisfactory’ was high in negative descriptive course evaluations. In addition, ‘class’ was expanded around the keywords ‘content’, ‘progress’, ‘time’, and ‘regrettable’. Third, the results of semantic network analysis between keywords in the lecture evaluation contents showed that in the positive type, ‘gratitude’, ‘class’, ‘hard work’, ‘explanation’, ‘student’, ‘kindness’, ‘help’, ‘understanding’, ‘assignment’, ‘time’ were the most important and connected keywords. In the negative course evaluation, keywords including ‘class’, ‘lecture’, ‘professor’, ‘assignment’, ‘disappointing’, ‘difficult’, ‘anxiety of test’ were analyzed as the most connected. Conclusions This study showed the possibility of suggesting directions for education improvement through descriptive lecture evaluation using sentiment analysis and semantic network analysis.