• 한국도서관정보학회지
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• 제47권3호
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• pp.95-114
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• 2016

이 연구의 목적은 특정한 독후감 사례들을 수집하고, 독후감 텍스트를 구성하는 키워드들을 대상으로 언어 네트워크를 구성하여, 독후감에 담겨있는 의미적 특성을 파악하는데 있다. 분석대상의 독후감은 전체 23편이며, 중등부 6편, 고등부 9편, 일반부 8편으로 구성된다. 3집단과 전체, 그리고 특정한 개별 독후감을 대상으로 키워드들을 선정하고, 동시출현관계를 바탕으로 하는 5가지 키워드 네트워크들을 구성하고 분석하였다. 분석결과는 다음과 같다. 첫째, 각 집단 및 개별 독후감의 키워드 네트워크들은 서로 다른 구조적인 특성을 나타내었다. 둘째, 3가지 중심성(연결정도 중심성, 근접 중심성, 매개 중심성)의 분석 결과 각 네트워크마다 중심성이 높은 키워드들이 다르게 나타났다. 이러한 특성은 독후감의 키워드 네트워크 분석이 개별 독후감뿐만 아니라 집단별 독후감들의 특성을 파악하는데 유용하다는 의미가 된다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제14권11호
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• pp.4426-4442
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• 2020

Since scene segmentation is becoming a hot topic in the field of autonomous driving and medical image analysis, researchers are actively trying new methods to improve segmentation accuracy. At present, the main issues in image semantic segmentation are intra-class inconsistency and inter-class indistinction. From our analysis, the lack of global information as well as macroscopic discrimination on the object are the two main reasons. In this paper, we propose a Densely connected residual Attention network (DA-Res2Net) which consists of a dense residual network and channel attention guidance module to deal with these problems and improve the accuracy of image segmentation. Specifically, in order to make the extracted features equipped with stronger multi-scale characteristics, a densely connected residual network is proposed as a feature extractor. Furthermore, to improve the representativeness of each channel feature, we design a Channel-Attention-Guide module to make the model focusing on the high-level semantic features and low-level location features simultaneously. Experimental results show that the method achieves significant performance on various datasets. Compared to other state-of-the-art methods, the proposed method reaches the mean IOU accuracy of 83.2% on PASCAL VOC 2012 and 79.7% on Cityscapes dataset, respectively.

• Architectural research
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• 제24권2호
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• pp.41-52
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• 2022

The purpose of this study is to grasp the understanding of smart cities and to review whether the common perception of smart cities, as people understand it, is changing over time. This study analyzes keywords related to smart cities used in social network services (SNSs) in 2011, 2016, and 2020 respectively through semantic network analysis. Smart city discussions appearing on SNS in 2011 mainly focused on technology, and the results of 2016 were generally similar to those of 2011. We can also find policy or business-oriented characteristics in emerging countries in 2020. We highlight that all the results of 2011, 2016, and 2020 have some correlation with each other through QAP(Quadratic Assignment Procedure) correlation analysis, and among them, the correlation between 2011 and 2016 is analyzed the most. The results of the frequency analysis, centrality analysis, and CONCOR(CONvergence of interaction CORrelation) analysis support these results. The results of this study help establish policies that reflect the needs and opinions of citizens in planning smart cities by identifying trends and paradigm transitions expressed by people in SNS. Furthermore, it is expected to help emerging countries by enhancing the understanding of the essence and trend of smart cities and to contribute by suggesting the direction of more sustainable technology development in future smart city policies for leading countries.

• 한국콘텐츠학회논문지
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• 제19권11호
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• pp.153-167
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• 2019

이번 연구는 지상파 TV, 중앙일간지, 지역지, 등 총 37개의 보도 매체의 2019년 강원도 대형 화재 보도를 분석하여 미디어의제를 파악하고 매체별, 시기별 미디어의제를 비교, 분석하였다. 토픽모델링 알고리즘과 의미망 분석을 활용한 연구는 네트워크 미디어의제의 구성을 분석하고 QAP 상관분석을 활용하여 매체간 의제 설정 효과도 검증하였다. 분석 결과, 2019년 강원도 화재 보도에서는 이재민 지원과 정치권 갈등 속성을 중심으로 다소 선정적인 미디어의제가 형성되었고 시기별, 매체별 미디어의제 간 유사성이 높은 것으로 나타났다. 이번 연구는 네트워크 의제설정 모델을 토대로 의미망 분석 도구를 활용해 대량의 기사를 분석하면서 기존의 빈도분석과는 구별되는 조사방법론을 구현한 연구라는 점에서 또 하나의 의미를 가질 수 있다.

• 한국의류학회지
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• 제46권6호
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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.

• 한국지구과학회지
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• 제34권2호
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• pp.173-186
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• 2013

본 연구의 목적은 언어네트워크분석을 이용하여 야외지질학습에서 학생들의 퇴적암에 대한 개념 구조 변화를 알아보기 위한 것이다. 이를 위하여 고등학생 15명을 대상으로 퇴적암에 대한 정의, 분류, 생성과정 및 특징을 묻는 개방형 문항을 개발하였으며, 이 텍스트 자료를 언어네트워크분석법을 통해 분석하였다. 그 결과 첫째, 야외지질학습을 통해 학생들의 퇴적암에 대한 개념 구조는 사전에 비해 사후에 크게 확장되었다. 둘째, 학생들의 개념 구조를 구성하는 하위 클러스터는 서로 긴밀하게 연결되어 있는 '작은 세상 네트워크'를 형성하였다. 셋째, 학생들의 개념 구조의 규모는 수개월이 지난 후 감소하였지만, 하위 클러스터의 연결 상태는 그대로 유지하고 있었다.

• International Journal of Contents
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• 제15권1호
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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.

• 한국초등과학교육학회지:초등과학교육
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• 제35권3호
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• pp.377-387
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• 2016

Whether textbooks faithfully reflect the curriculum contents is an important educational issue. The previous studies on the textbooks did not analyze the relationship described in the textbooks or the structure. In this regard, this study aims to analyze how the concept of life science area in the elementary school science textbooks developed on the basis of the 2009 revised curriculum is linked. In addition, it seeks to analyze how the concept presented in the learning content achievement standards of the curriculum is connected to other concepts. Towards this end, the conceptual linkage of eight units in the life science domain of elementary school science textbooks based on the 2009 revised curriculum was analyzed. The contents of the life science domain in the science textbooks were analyzed through a semantic network analysis, and the semantic network on the concept linked to the one described in curriculum's learning objectives was also analyzed. The results are as follows: 1) It will be difficult for students to understand the concept due to the complexity of the semantic network resulting from a number of concepts. 2) The curriculum's learning objectives presented in the curriculum are not faithfully reflected in the textbooks. 3) The textbooks are described on the basis of specific curriculum's learning objectives. Based on the findings of this study, the number of concepts described in the elementary school science textbooks needs to be significantly reduced so that the concepts can be meaningfully linked to each other.

• 한국콘텐츠학회논문지
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• 제17권11호
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• pp.371-382
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• 2017

본 연구는 콘텐츠산업정책을 포괄하는 문화정책에 대한 학술적 연구의 동향을 알고자 언어네트워크분석을 통해 국내의 가장 대표적인 문화정책 분야 전문학술지인 '문화정책논총'에 수록된 186편의 논문 주제어 832개를 대상으로 분석을 시도하였다. 시간적 범위는 한국연구재단 한국학술지인용색인 홈페이지(www.kci.go.kr)에 수록되어 있는 2008년 10월부터 2017년 1월까지로 하였다. 언어네트워크 분석은 주제어 빈도수, 밀도분석과 중심성을 지표로 분석하였으며, 이를 바탕으로 Netdraw 프로그램에 의한 시각화를 시도하였다. 언어네트워크분석 결과 가장 많은 빈도수를 기록한 주제어는 '문화'였고, '문화정책/행정', '문화산업/문화콘텐츠', '정책'이 최다의 빈도수를 기록한 그룹에 포함되었다. 빈도수가 높은 '문화정책/행정'과 '문화산업/문화콘텐츠'는 대부분의 중심성에서 우위를 차지했으나, 매개중심성은 낮아 다른 주제어들과의 중매 역할에는 한계를 드러냈다.

• 한국컴퓨터정보학회논문지
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• 제21권5호
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• pp.19-29
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• 2016

This paper suggests a method to refine a massive collective intelligence data, and visualize with multilevel sentiment network, in order to understand information in an intuitive and semantic way. For this study, we first calculated a frequency of sentiment words from each movie review. Second, we designed a Heatmap visualization to effectively discover the main emotions on each online movie review. Third, we formed a Sentiment-Movie Network combining the MDS Map and Social Network in order to fix the movie network topology, while creating a network graph to enable the clustering of similar nodes. Finally, we evaluated our progress to verify if it is actually helpful to improve user cognition for multilevel analysis experience compared to the existing network system, thus concluded that our method provides improved user experience in terms of cognition, being appropriate as an alternative method for semantic understanding.