• 제목/요약/키워드: communication centrality

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Emotional Expression of the Virtual Influencer "Luo Tianyi(洛天依)" in Digital'

  • Guangtao Song;Albert Young Choi
    • International Journal of Advanced Culture Technology
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    • 제12권2호
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    • pp.375-385
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    • 2024
  • In the context of contemporary digital media, virtual influencers have become an increasingly important form of socialization and entertainment, in which emotional expression is a key factor in attracting viewers. In this study, we take Luo Tianyi, a Chinese virtual influencer, as an example to explore how emotions are expressed and perceived through facial expressions in different types of videos. Using Paul Ekman's Facial Action Coding System (FACS) and six basic emotion classifications, the study systematically analyzes Luo Tianyi's emotional expressions in three types of videos, namely Music show, Festivals and Brand Cooperation. During the study, Luo Tianyi's facial expressions and emotional expressions were analyzed through rigorous coding and categorization, as well as matching the context of the video content. The results show that Enjoyment is the most frequently expressed emotion by Luo Tianyi, reflecting the centrality of positive emotions in content creation. Meanwhile, the presence of other emotion types reveals the virtual influencer's efforts to create emotionally rich and authentic experiences. The frequency and variety of emotions expressed in different video genres indicate Luo Tianyi's diverse strategies for communicating and connecting with viewers in different contexts. The study provides an empirical basis for understanding and utilizing virtual influencers' emotional expressions, and offers valuable insights for digital media content creators to design emotional expression strategies. Overall, this study is valuable for understanding the complexity of virtual influencer emotional expression and its importance in digital media strategy.

Network Analysis of East Asian Research in South Korea for the 2004-2013 Period

  • Park, Ji-Young;Park, Han Woo
    • International Journal of Contents
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    • 제11권1호
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    • pp.52-61
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    • 2015
  • In the past decade, East Asian Research has received attention from researchers as well as in South Korea society-at-large. The broad category of East Asian Research includes various disciplinary fields, such as "history, economics, and politics; however, few studies have used quantitative analysis to explore its development. In this paper, we used network analysis to identify the disciplines and active research areas, focusing on productivity, collaboration patterns, and citation networks of East Asian Research in South Korea. For this study, 6,646 journal publications related with East Asian Research and indexed by KCI (Korean Citation Index) during the 10-year period of 2004-2013 were considered. Results show that East Asian Research was led during this period by sole-researchers, rather than interdisciplinary studies. Moreover, a co-institution network represents active institutions with a high degree and collaborative centrality. In terms of journal-journal citation networks, journals belonging to both "history" and "Korean literature" disciplines were dominant.

Deep Learning Document Analysis System Based on Keyword Frequency and Section Centrality Analysis

  • Lee, Jongwon;Wu, Guanchen;Jung, Hoekyung
    • Journal of information and communication convergence engineering
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    • 제19권1호
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    • pp.48-53
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    • 2021
  • Herein, we propose a document analysis system that analyzes papers or reports transformed into XML(Extensible Markup Language) format. It reads the document specified by the user, extracts keywords from the document, and compares the frequency of keywords to extract the top-three keywords. It maintains the order of the paragraphs containing the keywords and removes duplicated paragraphs. The frequency of the top-three keywords in the extracted paragraphs is re-verified, and the paragraphs are partitioned into 10 sections. Subsequently, the importance of the relevant areas is calculated and compared. By notifying the user of areas with the highest frequency and areas with higher importance than the average frequency, the user can read only the main content without reading all the contents. In addition, the number of paragraphs extracted through the deep learning model and the number of paragraphs in a section of high importance are predicted.

디지털 커뮤니케이션 환경에서 청소년들의 감정과 이모티콘의 관계 (Relationship between emotions and emoticons in adolescents in digital communication environment)

  • 김윤지;강동묵;김주영;김종은
    • 의료커뮤니케이션
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    • 제12권1호
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    • pp.51-72
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    • 2017
  • Purpose: Adolescents use emoticons to express their emotions in an online environment. Hence, medical experts can understand the emotions of adolescents by emoticons. The goal of this study was to investigate the relationship between various emotions and emoticons among the Korean adolescents. Methods: The questionnaire survey was conducted between September 1 and 30, 2014, involving 3,272 students in elementary schools, middle schools, and high schools affiliated in the Department of Education of the metropolitan city of Busan. A total of 1,717 students responded to the survey. The participants consisted of 806 males (46.9%), and 911 females (53.1%). Among these, there were 557 elementary school students (32.4%), 617 middle school students (35.9%), and 543 high school students (31.6%). A social networking analysis was conducted using NodeXL. Results: The frequency of emoticon use among adolescents runs in the order of joy, sadness, fear, surprise, anger, disgust, and then depression. Elementary school females mainly use emoticons to express joy; middle school females use emoticons to express sadness, surprise, anger, disgust, and depression; and high school females use emoticons to express fear. Age- and gender-specific emoticon networks were visualized by using the Haren-Korel fast multiscale algorithm. Commonly used emoticons by age and gender were expressed in the networks. Results of age- and gender-specific emoticon networks visualization show similar results of centrality of seven emoticons. Conclusion: In the digital communication environment, emoticons could be used to catch the emotions of adolescents in Korea.

의미 연결망 분석을 활용한 대학 홈페이지 FAQ 개선방안 (Improving University Homepage FAQ Using Semantic Network Analysis)

  • 안수현;이상준
    • 디지털융복합연구
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    • 제16권9호
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    • pp.11-20
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    • 2018
  • 민원 질의응답의 소통수단으로 보편화된 Q&A 게시판에는 반복된 질문들이 자주 등록되어 민원업무를 효율적으로 관리할 필요성이 제기된다. 본 연구는 대학 홈페이지의 Q&A 게시판에 게재된 비정형 데이터를 중심으로 학생 중심의 질의응답집(FAQ)을 구성하고자 한다. 이에 최근 3년간 690건의 게시물에서 주요 핵심어를 추출하고 의미 연결망 분석을 통해 중심성 분석 및 핵심어 사이의 관계성을 파악하여 네트워크 시각화를 진행하였다. 분석결과 민원질의에서 가장 중심성이 높은 핵심어는 신청, 교과목, 학점, 이수, 졸업, 승인, 기간, 전공, 포털, 학과 등의 순이었다. 또한 주요 핵심어들은 수업, 학적, 학생활동, 장학금, 도서관, 생활관, 정보화, 통학 영역의 8개 군집으로 구분되었다. 이를 토대로 질의횟수가 많은 내용을 분야별로 정리하여 FAQ를 구성한다면 반복적인 질문에 대한 민원응대 프로세스를 간소화함으로써 수요자의 편의성과 행정의 효율성 향상에 기여하고 나아가 대학 구성원간의 원활한 양방향 소통이 가능할 것으로 기대한다.

헬스케어 특허의 IPC 코드 기반 사회 연결망 분석(SNA)을 이용한 기술 융복합 분석 (Technology Convergence Analysis by IPC Code-Based Social Network Analysis of Healthcare Patents)

  • 심재륜
    • 한국정보전자통신기술학회논문지
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    • 제15권5호
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    • pp.308-314
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    • 2022
  • 본 연구는 국내에 출원된 헬스케어 특허의 기술 융복합 분석에 관한 것으로 사회 연결망 분석(Social Network Analysis)을 이용하여 핵심 기술간 관계를 시각화하였다. 헬스케어 특허의 서브클래스 수준에서 복합 IPC 코드를 가지는 특허는 1,155건(49.4%)으로 조사되었고, 이를 대상으로 사회 연결망 분석을 실시한 결과 연결 중심성이 가장 큰 IPC 코드는 A61B, G16H, G06Q 순이고, 매개 중심성이 가장 큰 IPC 코드는 A61B, G16H, G06Q 순이다. 또한 헬스케어 특허는 두 개의 큰 기술 집합(Cluster)으로 구성되어 있다는 것을 확인할 수 있었다. Cluster-1은 A61B와 G16H 및 G06Q를 중심으로 헬스케어 인포매틱스 관련 기술을 이용한 진단, 수술 등 관련 비즈니스 모델에 해당하고, Cluster-2는 H04L과 H04W 및 H04B로 구성된 디지털 통신 기반의 헬스케어 사물인터넷 기술이다. 헬스케어 특허의 기술 융복합 핵심 쌍은 Cluster-1에서 [G16H-A61B]와 [G16H-G06Q] 이고, Cluster-2에서는 [H04L-H04W] 이다. 본 연구는 헬스케어 특허의 기술 개발 동향과 앞으로의 특허 출원에 기여할 수 있다.

시골장터 기반 로컬 커뮤니티가 지역활성화에 미치는 영향에 대한 온라인 네트워크 분석 (Online Network Analysis of the Impact of Local Market-based Communities on Regional Revitalization)

  • 박정선;박상혁;오승희
    • 한국정보시스템학회지:정보시스템연구
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    • 제33권1호
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    • pp.45-68
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    • 2024
  • Purpose This paper examines the role of local market-based communities in driving regional revitalization, using detailed analysis of online networks. We aim to dissect a local community's communication network, highlighting members with high engagement levels and exploring their characteristics. Our goal is to identify the conditions that allow local community networks to grow independently and to demonstrate how the activation of these networks contributes to regional revitalization. Design/methodology/approach We employ a mixed-methods approach, combining social network analysis with statistical techniques to investigate the structure of online communication networks. Specifically, we use ANOVA to determine the statistical significance of our findings, ensuring their reliability. To complement our quantitative data, we include qualitative insights from interviews, adding depth and context to our analysis. Findings Our results show that individuals with high centrality in the online network are crucial for maintaining active local communities. We find that leveraging local resources to create a supportive and adaptable environment is essential for the communities' sustainability and expansion. Importantly, our research draws a direct connection between the vitality of local community networks and the broader process of regional revitalization. We argue that energizing local communities is an effective way to address the risk of regional decline. By integrating quantitative analysis with qualitative feedback, this study contributes to the understanding of local market-based communities as key drivers of regional development. It emphasizes the importance of building vibrant, resourceful community networks to revitalize areas experiencing socio-economic challenges.

아파트 공동체 주민참여의 사회관계 분석 - 서울특별시 거주자를 중심으로 - (Analysis of the Social Relationship of Apartment Community Residents' Participation - Focused on Residents in Seoul City -)

  • 김해숙;정복환;이재성
    • 한국주거학회논문집
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    • 제25권6호
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    • pp.75-84
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    • 2014
  • The purpose of this study was to identify a direction for increase of resident participation by analyzing the social relations of resident participation. In the research method, the method of statistical analysis was added to the legal institutional method. As a result, the following findings were obtained: First, it is very important that the resident representative meeting at the center of the participation of the resident organization should take the role in and responsibility for the promotion of participation. Second, it is necessary to have smooth communication with voluntary groups such as women's association or club forming the coordinating group. Third, Among other things, it is judged that residents should have an active will to participate and practice in order to promote their participation in the apartment community. The above results imply that participation should be promoted by enabling residents to perform four functions of resident participation. Accordingly, the promotion of participation based on the function of participation is very necessary and important.

지연 감내 네트워크에서 사회관계기반 기회적 라우팅 기법 (An Opportunistic Routing Scheme Based on Social Relations in Delay-Tolerant Networks)

  • 김찬명;강인석;오영준;한연희
    • 정보처리학회논문지:컴퓨터 및 통신 시스템
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    • 제3권1호
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    • pp.15-22
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    • 2014
  • 지연 감내 네트워크는 지속적인 연결이 보장되지 않고 저장(Store), 운반(Carry), 전달(Forward) 방식의 메시지 전달을 사용 하는 네트워크이다. 이러한 지연 감내 네트워크에서 메시지 전달은 중요한 연구 이슈이며, 최근 많은 라우팅 기법들이 제안되었다. 본 논문에서는 노드들의 사회관계와 확장 매개 중심도를 이용하여 효율적인 지연 감내 네트워크에서 라우팅 기법을 제안한다. 시뮬레이션 결과를 통해 Epidemic routing, Friendship routing에 비해 적은 메시지 전달 성공률차이를 유지하며, 메시지 전달 비용에는 효율적임을 보인다.

플립러닝 연구 동향에 대한 키워드 네트워크 분석 연구 (A Study on the Research Trends to Flipped Learning through Keyword Network Analysis)

  • 허균
    • 수산해양교육연구
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    • 제28권3호
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    • pp.872-880
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    • 2016
  • The purpose of this study is to find the research trends relating to flipped learning through keyword network analysis. For investigating this topic, final 100 papers (removed due to overlap in all 205 papers) were selected as subjects from the result of research databases such as RISS, DBPIA, and KISS. After keyword extraction, coding, and data cleaning, we made a 2-mode network with final 202 keywords. In order to find out the research trends, frequency analysis, social network structural property analysis based on co-keyword network modeling, and social network centrality analysis were used. Followings were the results of the research: (a) Achievement, writing, blended learning, teaching and learning model, learner centered education, cooperative leaning, and learning motivation, and self-regulated learning were found to be the most common keywords except flipped learning. (b) Density was .088, and geodesic distance was 3.150 based on keyword network type 2. (c) Teaching and learning model, blended learning, and satisfaction were centrally located and closed related to other keywords. Satisfaction, teaching and learning model blended learning, motivation, writing, communication, and achievement were playing an intermediary role among other keywords.