• Title/Summary/Keyword: SNA(Semantic Network Analysis)

Search Result 14, Processing Time 0.027 seconds

An Analysis of Conceptual Structure in the Subjects related to Matter of Elementary School Pre-service Teachers using SNA Method (의미네트워크를 활용한 초등학교 예비교사들의 물질 개념체계 분석)

  • Kim, Do Wook
    • Journal of Korean Elementary Science Education
    • /
    • v.37 no.1
    • /
    • pp.39-53
    • /
    • 2018
  • The purpose of this study was to investigate the conceptual structure of subjects related to matter having pre-service elementary school teachers by applying semantic network analysis (SNA). The analyzed concepts in the subjects of matter were 6 words such as 'atom', 'molecule', 'ion', 'electron', 'matter' and 'particle'. The results of SNA of the concepts are as follows : 1. In the semantic network of 'atom', words having a high betweenness centrality were linked with the words based on both the scientific context and the everyday context. 2. The network of 'molecule' was analyzed to be more organized than the network of the 'atom'. 3. In the network of 'ion', the group of words of the scientific context was distinguished from the group of words of the everyday context. 4. The network of 'electron' was analyzed to be more oriented on electricity and magnetism in the field of physics. 5. In the network of 'matter', the words related to compounds were linked with knowledge of history of science. 6. The network of 'particle' was not structured with words based on particulate nature of matter.

Semantic Network Analysis of Science Gifted Middle School Students' Understanding of Fact, Hypothesis, Theory, Law, and Scientificness (언어 네트워크 분석법을 통한 중학교 과학영재들의 사실, 가설, 이론, 법칙과 과학적인 것의 의미에 대한 인식 조사)

  • Lee, Jun-Ki;Ha, Minsu
    • Journal of The Korean Association For Science Education
    • /
    • v.32 no.5
    • /
    • pp.823-840
    • /
    • 2012
  • The importance of teaching the nature of science (NOS) has been emphasized in the science curriculum, especially in the science curriculum for science-gifted students. Nevertheless, few studies concerning the structure and formation of students' mental model on NOS have been carried out. This study aimed to explore science-gifted students' understanding of 'fact', 'hypothesis', 'theory', 'law', and 'scientificness' by utilizing semantic network analysis. One hundred ten science-gifted middle school students who were selected by a national university participated in this study. We collected students' written responses of five items and analyzed them by the semantic network analysis(SNA) method. As a result, the core ideas of students' understanding of 'fact' were proof and reality, of 'hypothesis' were tentativeness and uncertainty, of 'theory' was proven hypothesis by experimentation, of 'law' were absoluteness and authority, and of 'scientificness' were factual evidence, verifiability, accurate and logical theoretical framework. The result of integrated semantic network illustrated that the viewpoint of science-gifted students were similar to absolutism and logical positivism (empiricism). Methodologically, this study showed that the semantic network analysis method was an useful tool for visualization of students' mental model of scientific conceptions including NOS.

Quantitative Study of Soft Masculine Trends in Contemporary Menswear Using Semantic Network Analysis

  • Tin Chun Cheung;Sun Young Choi
    • Journal of the Korean Society of Clothing and Textiles
    • /
    • v.46 no.6
    • /
    • pp.1058-1073
    • /
    • 2022
  • Big data analytics and social media have shifted the way fashion trends are dictated. Fashion as a medium for expressing gender has created new concepts of masculinity in popular culture, where men are increasingly depicted in a softer style. In this study, we analyzed 2,879 menswear collections over a 10-year period from Vogue US to uncover key menswear trends. Using Semantic Network Analysis (SNA) on Orange3, we were able to quantitatively analyze how contemporary menswear designers interpreted diversified trends of masculinity on the runway. Frequency and degree centrality were measured to weigh the significance of trend keywords. "Jacket (f = 3056; DC = 0.80), shirt (f = 1912; DC = 0.60) and pant (f = 1618; DC = 0.53)" were among the most prominent keywords. Our results showed that soft masculine keywords, e.g., "lace, floral, and pink" also appeared, but with the majority scoring DC = < 0.10. The findings provide an insight into key menswear trends through frequency, degree centrality measurements, time-series analysis, egocentric, and visual semantic networks. This also demonstrates the feasibility of using text analytics to visualize design trends, concepts, and patterns for application as an ideation tool for academic researchers, designers, and fashion retailers.

Building and Analysis of Semantic Network on S&T Multilingual Terminology (과학기술 전문용어의 다국어 의미망 생성과 분석)

  • Jeong, Do-Heon;Choi, Hee-Yoon
    • Journal of Information Management
    • /
    • v.37 no.4
    • /
    • pp.25-47
    • /
    • 2006
  • A terminology system capable of providing interpretations and classification information on a multilingual science and technology(S&T) terminology is essential to establish an integrated search environment for multilingual S&T information systems. This paper aims to build a base system to manage an integrated information system for multilingual S&T terminology search. It introduces a method to build a search system for S&T terminologies internally linked through the multilingual semantic network and a search technique on the multiple linked nodes. In order to provide a foundation for further analysis researches, it also attempts to suggest a basic approach to interpret terminology clusters generated with those two search methods.

The Periodical Trend of Urban Regeneration through Mass Media - Focused on the 1920s and 1990s - (매스미디어를 통해 본 도시재생의 시대적 동향 - 1920년대~1990년대를 중심으로 -)

  • Kim, Sa-rang;Lee, Jeong
    • Journal of the Korean Institute of Landscape Architecture
    • /
    • v.47 no.2
    • /
    • pp.28-48
    • /
    • 2019
  • This research is aimed at identifying the perception associated with urban regeneration and predicting policy implications of future directions by analyzing the trend of urban regeneration depicted in the mass media by utilizing SNA (Semantic-Network Analysis) techniques. As the number of articles has increased, it is noted through analysis that the interrelationships between social phenomena and issues have combined to form the meaning of urban regeneration. Overall, 'urban' and 'regeneration' keywords also appeared at different periods, with 'urban' closely related to 'regeneration' starting in 1970 when urbanization was becoming more prevalent. It was analyzed that the frequency of 'urban' appeared more frequently in the early 1990s, while the frequency of 'rural' decreased sharply. Until the 1990s, the slums and the recession that appeared as side effects of urban problem-solving policies were mostly concentrated in cities. Policy discussions were conducted with the goal of improving the physical environment of cities rather than concentrating on the surrounding rural areas. The distributions of the keywords 'development' and 'regeneration' have increased quantitatively since the 1970s, and urban polarization has exploded due to the development of the external growth of cities, mirroring the trend of accelerated environmental threats. In particular, the keywords for 'regeneration' emerged mainly related to environmental problems, which led to the need for urban regeneration, and environmentally and ecologically friendly development. The emergence of "urban," "regeneration" and "environment" as keywords having to do with urban regeneration grew in the 1990s. This suggests that urban regeneration is now linked to "environment", as that has become a social issue.

An Expert Recommendation System using Ontology-based Social Network Analysis (온톨로지 기반 소설 네트워크 분석을 이용한 전문가 추천 시스템)

  • Park, Sang-Won;Choi, Eun-Jeong;Park, Min-Su;Kim, Jeong-Gyu;Seo, Eun-Seok;Park, Young-Tack
    • Journal of KIISE:Computing Practices and Letters
    • /
    • v.15 no.5
    • /
    • pp.390-394
    • /
    • 2009
  • The semantic web-based social network is highly useful in a variety of areas. In this paper we make diverse analyses of the FOAF-based social network, and propose an expert recommendation system. This system presents useful method of ontology-based social network using SparQL, RDFS inference, and visualization tools. Then we apply it to real social network in order to make various analyses of centrality, small world, scale free, etc. Moreover, our system suggests method for analysis of an expert on specific field. We expect such method to be utilized in multifarious areas - marketing, group administration, knowledge management system, and so on.

Comparing the Structure of Secondary School Students' Perception of the Meaning of 'Experiment' in Science and Biology (중등학생들의 과학과 생물에서의 '실험'의 의미에 대한 인식구조 비교)

  • Lee, Jun-Ki;Shin, Sein;Ha, Minsu
    • Journal of The Korean Association For Science Education
    • /
    • v.35 no.6
    • /
    • pp.997-1006
    • /
    • 2015
  • Perception of the experiment is one of the most important factors of students' understanding of scientific inquiry and the nature of science. This study examined the perception of middle and high school students of the meaning of 'experiment' in the biological sciences. Semantic network analysis (SNA) was especially used to visualize students' perception structure in this study. One hundred and ninety middle school students and 200 high school students participated in this study. Students responded to two questions on the meaning of 'experiment' in science and biology. This study constructed four semantic networks based on the collected response. As a result, middle school students about the 'experiment' in science are 'we', 'direct', 'principle' of such words was aware of the experiments from the center to the active side. The high school students' 'theory', 'true', 'information' were recognized as an experiment that explores the process of creating a knowledge center including the word. In addition, middle school students relative to 'experiment' of the creature around the 'dissection', 'body', high school students were recognized as 'life', 'observation' observation activities dealing with the living organisms and recognized as a core. The results of this study will be used as important evidence in the future to map out an experiment in biological science curriculum.

Comparing Corporate and Public ESG Perceptions Using Text Mining and ChatGPT Analysis: Based on Sustainability Reports and Social Media (텍스트마이닝과 ChatGPT 분석을 활용한 기업과 대중의 ESG 인식 비교: 지속가능경영보고서와 소셜미디어를 기반으로)

  • Jae-Hoon Choi;Sung-Byung Yang;Sang-Hyeak Yoon
    • Journal of Intelligence and Information Systems
    • /
    • v.29 no.4
    • /
    • pp.347-373
    • /
    • 2023
  • As the significance of ESG (Environmental, Social, and Governance) management amplifies in driving sustainable growth, this study delves into and compares ESG trends and interrelationships from both corporate and societal viewpoints. Employing a combination of Latent Dirichlet Allocation Topic Modeling (LDA) and Semantic Network Analysis, we analyzed sustainability reports alongside corresponding social media datasets. Additionally, an in-depth examination of social media content was conducted using Joint Sentiment Topic Modeling (JST), further enriched by Semantic Network Analysis (SNA). Complementing text mining analysis with the assistance of ChatGPT, this study identified 25 different ESG topics. It highlighted differences between companies aiming to avoid risks and build trust, and the general public's diverse concerns like investment options and working conditions. Key terms like 'greenwashing,' 'serious accidents,' and 'boycotts' show that many people doubt how companies handle ESG issues. The findings from this study set the foundation for a plan that serves key ESG groups, including businesses, government agencies, customers, and investors. This study also provide to guide the creation of more trustworthy and effective ESG strategies, helping to direct the discussion on ESG effectiveness.

Analysis of Images of Middle School Students' Preference and Avoidance of Science Teachers by Class Situation Using Semantic Network Analysis (언어 네트워크 분석을 활용한 중학생들의 과학 교사에 대한 수업 상황별 선호, 기피 이미지 분석)

  • Cho, Yunjung;Kim, Youngshin;Lim, Soo-min
    • Journal of Science Education
    • /
    • v.45 no.1
    • /
    • pp.55-68
    • /
    • 2021
  • The modern society is rapidly changing, and accordingly, the required teacher image is changing as well. Middle school students are immature, when they undergo major changes both physically and mentally, and teachers have a great influence. How students perceive the teacher determines the relationship between teachers and students. Therefore, it is necessary to analyze what kind of teacher image middle school students want. The purpose of this study is to analyze the image of a science teacher who prefers and avoids each class situation perceived by middle school students. To this end, 502 middle school students were divided into five classes: class type, class material presentation method, subject instruction method, subject content explanation method, and class atmosphere, and the image of science teacher who prefers and avoids is described in an open format. Concepts presented by middle school students were analyzed through semantic network analysis (SNA). The conclusions of this study are as follows: first, in order to make middle school students interested in science, an inquiry-centered experiment class should be conducted. Second, the change of class by science teacher can change it into preferred science class. Third, student-centered classes should be conducted according to the level so that students can understand. Finally, science teachers continue to strive through communication between science teachers and students, and students and students, and look forward to changes in science classes through this.

Analysis of OpinionMining on Consumer Satisfaction of InternetBanks: Focusing on the app review (인터넷전문은행의 소비자 만족에 관한 오피니언 마이닝 분석: 앱 사용 후기 중심으로)

  • Lee, Jong Hwa;Lee, Hyun Kyu
    • The Journal of Information Systems
    • /
    • v.32 no.3
    • /
    • pp.151-164
    • /
    • 2023
  • Purpose This study aims to analyze the current status of consumer awareness on Internet banks by conducting a full investigation and collecting user opinions presented on Google Play. After cateogorizing the current dissatisfaction, we would like to present not only the direction of the Internet bank service of but also the improvements of the platform. Design/methodology/approach Using opinion mining, subjectivity analysis, polarity analysis, and polarity information analysis of comments were conducted step by step to extract negative and positive keywords. The extracted keywords analyzed the weights of the frequently appearing positive and negative keywords using the TF-IDF model. Based on previous studies that negative information is more sensitive to positive information, we tried to confirm the connection, proximity, and mediation of negative keywords. Semantic Network Analysis (SNA) was used to visualize the connection relationship between the negative comment keywords of the three Internet banks. Findings Domestic Internet banks such as Kakao Bank, K-Bank, and Toss Bank have attracted a lot of attention even before they were established, and after establishment, they have secured a wide range of users through platforms that are completely different from existing banks. This study found out that the convenience of the app affects the opening and transaction of non-face-to-face accounts, which are characteristics of domestic Internet banks, which also affects the bank's business strategy. In addition, this study shows that the business characteristics of the company can be identified.