• Title/Summary/Keyword: semantic network

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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
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    • v.46 no.6
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    • pp.1058-1073
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    • 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.

An Analysis of Scientific Concepts Pre-service Elementary School Teachers Have through Semantic Network Analysis (의미 네트워크 분석법을 활용한 초등 예비교사들이 생각하는 과학에 대한 의미 분석)

  • Kim, Dong-Ryeul
    • Journal of Korean Elementary Science Education
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    • v.32 no.3
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    • pp.327-345
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    • 2013
  • This study aims to investigate how pre-service elementary school teachers understand 'something scientific', 'being scientific', 'scientific events' and 'scientific questions' through semantic network analysis. To achieve this purpose, this study carried out a central analysis of the frequency and density of words and the degree of connection between key words, a concentric analysis, a click analysis and a common network analysis through text semantic network analysis by using NetMiner 4.0 Program. Based on the results of these analyses, this study came to the following conclusions. Firstly, in perceiving 'something scientific', pre-service elementary school teachers recognized 'verification', 'objective' and 'experiment' as most important words. In other words, they perceived that main grounds for something scientific should be provided through clear facts, possible to be verified and accompanied by an exact and logical theoretical system. In regard to 'being scientific', they perceived 'explanation', 'objective' and 'verification' as most important words, while having a traditional point of view that science is a set that can be explained objectively. Secondly, in regard that the term, 'observation', is contained in 'scientific events', they showed a high rate of understanding it as a scientific event. In regard to scientifical reasons, they showed the highest frequency of 'observation', and for unscientific reasons, they showed the highest frequency of 'behavior'. In perceiving 'scientific questions', they showed the highest frequency of determining bacteria-related questions as scientific. As a reason why they thought as scientific, they mentioned 'observation' most frequently like 'scientific events', while mentioning 'value judgement' as a reason why they thought as unscientific most frequently. From the results of integrated network analysis, this study found out that words pre-service teachers commonly used in stating scientific events or scientific questions were overlapped with words they mentioned for scientific events or scientific questions. As a result, it was found there were many pre-service teachers having interpreted scientific words without clearly distinguishing scientific events or scientific questions.

An Analysis of the Changes of High School Students' Conceptual Structure about Sedimentary Rocks before and after the Field Trip using the Semantic Network Analysis (언어네트워크분석을 이용한 야외지질학습 전후의 퇴적암에 대한 개념 구조 변화 분석)

  • Park, Kyeong Jin;Chung, Duk Ho;Cho, Kyu Seong
    • Journal of the Korean earth science society
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    • v.34 no.2
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    • pp.173-186
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    • 2013
  • The purpose of the study was to investigate the change of students' conceptual structures about sedimentary rocks through the field trip. A semantic network analysis method was utilized to assess the change. An open-ended questionnaire was developed to assess high school students' knowledge of sedimentary rock including its definition, classification, formation process, and characteristics. Fifteen high school students participated in the field trip of this study. The text data were analyzed using the semantic network analysis method. Results are as follows. First, high school students' conceptual structures about sedimentary rocks were more expanded after the field trip. Second, students' conceptual structures formed a 'small world network' by combining the sub-clusters. Third, the size of students' conceptual structures was decreased after a few month of field trip. Nonetheless, the connection among the clusters remained the same.

Semantic Segmentation using Convolutional Neural Network with Conditional Random Field (조건부 랜덤 필드와 컨볼루션 신경망을 이용한 의미론적인 객체 분할 방법)

  • Lim, Su-Chang;Kim, Do-Yeon
    • The Journal of the Korea institute of electronic communication sciences
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    • v.12 no.3
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    • pp.451-456
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    • 2017
  • Semantic segmentation, which is the most basic and complicated problem in computer vision, classifies each pixel of an image into a specific object and performs a task of specifying a label. MRF and CRF, which have been studied in the past, have been studied as effective methods for improving the accuracy of pixel level labeling. In this paper, we propose a semantic partitioning method that combines CNN, a kind of deep running, which is in the spotlight recently, and CRF, a probabilistic model. For learning and performance verification, Pascal VOC 2012 image database was used and the test was performed using arbitrary images not used for learning. As a result of the study, we showed better partitioning performance than existing semantic partitioning algorithm.

Semantic Network Analysis of 2019 Gangwon-do Wild Fire News Reporting: Focusing on Media Agenda Analysis (2019년 강원도 화재 보도에 대한 언어망 분석: 미디어의제 분석을 중심으로)

  • Lee, Jeng Hoon
    • The Journal of the Korea Contents Association
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    • v.19 no.11
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    • pp.153-167
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    • 2019
  • This study aims to identify the media agenda and to compare each media agenda by media and by time period, analyzing the news about 2019 Gangwon-do's wild fire reported by 37 Korean news media. Using the topic modeling algorithm and semantic network analysis, this study inspected the configuration of the network media agenda and examined the intermedia agenda setting effect by using QAP correlation analysis. Results showed that the sensational media agenda with the attributes such as victim aid and political conflict and the similarity of each media agenda for this disaster reporting.

Study on Agenda-Setting Structure between SNS and News: Focusing on Application of Network Agenda-Setting

  • Kweon, Sang-Hee;Go, Taeseong;Kang, Bo-young;Cha, Min-Kyung;Kim, Se-Jin;Kweon, Hea-Ji
    • International Journal of Contents
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    • v.15 no.1
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    • pp.10-24
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    • 2019
  • This study applied network agenda-setting theory to analyze the impact of the agenda-setting function of the media on certain issues by focusing on the agenda at the center of controversy, 'Creative Economy'. To this end, the study extracted the data referred to creative economy in the media and SNS from 1 January 2008 to 31 December 2014, and analyzed the data using the network analysis program UCINET and the Korean language analysis program Textom. The results of the present study show that, during the period under former President Lee (2008-2011), the media's creative economy agenda-setting function did not exert a significant impact on the agenda-setting within SNS. However, from 2012 when the government of former President Park Geun-hye had started, the agenda-setting function of the media starts to show increasingly strong influence on the agenda cognition in SNS. The central words and sub-words configuration forming the center of the semantic network moved in the direction of a high correlation, in addition to the gradually increasing correlation based on QAP correlation analysis. In 2014, the semantic networks of the media and SNS bore a close resemblance to each other, while the shape of networks and sub-words structure also had a high level of similarity.

Estimating Media Environments of Fashion Contents through Semantic Network Analysis from Social Network Service of Global SPA Brands (패션콘텐츠 미디어 환경 예측을 위한 해외 SPA 브랜드의 SNS 언어 네트워크 분석)

  • Jun, Yuhsun
    • Journal of the Korean Society of Clothing and Textiles
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    • v.43 no.3
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    • pp.427-439
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    • 2019
  • This study investigated the semantic network based on the focus of the fashion image and SNS text utilized by global SPA brands on the last seven years in terms of the quantity and quality of data generated by the fast-changing fashion trends and fashion content-based media environment. The research method relocated frequency, density and repetitive key words as well as visualized algorithms using the UCINET 6.347 program and the overall classification of the text related to fashion images on social networks used by global SPA brands. The conclusions of the study are as follows. A common aspect of global SPA brands is that by looking at the basis of text extraction on SNS, exposure through image of products is considered important for sales. The following is a discriminatory aspect of global SPA brands. First, ZARA consistently exposes marketing using a variety of professions and nationalities to SNS. Second, UNIQLO's correlation exposes its collaboration promotion to SNS while steadily exposing basic items. Third, in the case of H&M, some discriminatory results were found with other brands in connectivity with each cluster category that showed remarkably independent results.

A Study on Research Trend for Nurses' Workplace Bullying in Korea: Focusing on Semantic Network Analysis and Topic Modeling (간호사의 직장 내 괴롭힘에 대한 국내 연구 동향 분석: 의미연결망분석과 토픽모델링 중심)

  • Choi, Jeong Sil;Kim, Youngji
    • Korean Journal of Occupational Health Nursing
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    • v.28 no.4
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    • pp.221-229
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    • 2019
  • Purpose: The aim of this study was to identify core keywords and topic groups of workplace bullying researches in the past 10 years for better understanding research trend. Methods: The study was conducted in four steps: 1) collecting abstracts, 2) extracting and cleaning semantic morphemes, 3) building co-occurrence matrix and 4) analyzing network features and clustering topic groups. Results: 437 articles between 2010 and 2019 were retrieved from 5 databases (RISS, NDSL, Google scholar, DBPIA and Kyobo Scholar). Forty-one abstracts from these articles were extracted, and network analysis was conducted using semantic network module. The most important core keywords were 'turnover', 'intention', 'factor', 'program' and 'nursing'. Four topic groups were identified from Korean databases. Major topics were 'turnover' and 'organization culture'. Conclusion: After reviewing previous research, it has been found that turnover intention has been emphasized. Further research focused on various intervention is needed to relieve workplace bullying in nursing field.

A Word Sense Disambiguation Method with a Semantic Network (의미네트워크를 이용한 단어의미의 모호성 해결방법)

  • DingyulRa
    • Korean Journal of Cognitive Science
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    • v.3 no.2
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    • pp.225-248
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    • 1992
  • In this paper, word sense disambiguation methods utilizing a knowledge base based on a semantic network are introduced. The basic idea is to keep track of a set of paths in the knowledge base which correspond to the inctemental semantic interpretation of a input sentence. These paths are called the semantic paths. when the parser reads a word, the senses of this word which are not involved in any of the semantic paths are removed. Then the removal operation is propagated through the knowledge base to invoke the removal of the senses of other words that have been read before. This removal operation is called recusively as long as senses can be removed. This is called the recursive word sense removal. Concretion of a vague word's concept is one of the important word sense disambiguation methods. We introduce a method called the path adjustment that extends the conctetion operation. How to use semantic association or syntactic processing in coorporation with the above methods is also considered.

Modern Linguistics: Theoretical Aspects of the Development of Cognitive Semantics

  • Nataliia Mushyrovska;Liudmyla Yursa;Oksana Neher;Iryna Pavliuk
    • International Journal of Computer Science & Network Security
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    • v.23 no.6
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    • pp.162-168
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    • 2023
  • This article presents an examination of the major cognitive-semantic theories in linguistics (Langacker, Lakoff, Fillmore, Croft). The CST's foundations are discussed concerning the educational policy changes, which are necessary to improve the linguistic disciplines in the changing context of higher education, as well as the empowerment and development of the industry. It is relevant in the light of the linguistic specialists' quality training and the development of effective methods of language learning. Consideration of the theories content, tools, and methods of language teaching, which are an important component of quality teaching and the formation of a set of knowledge and skills of students of linguistic specialties, remains crucial. This study aims to establish the main theoretical positions and directions of cognitive-semantic theory in linguistics, determine the usefulness of teaching the basics of cognitive linguistics, the feasibility of using methods of cognitive-semantic nature in the learning process. During the research, the methods of linguistic description and observation, analysis, and synthesis were applied. The result of the study is to establish the need to study basic linguistic theories, as well as general theoretical precepts of cognitive linguistics, which remains one of the effective directions in the postmodern mainstream. It also clarifies the place of the main cognitive-semantic theories in the teaching linguistics' practice of the XXI century.