• Title/Summary/Keyword: TextMining

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Trends and Future Directions in Facial Expression Recognition Technology: A Text Mining Analysis Approach (얼굴 표정 인식 기술의 동향과 향후 방향: 텍스트 마이닝 분석을 중심으로)

  • Insu Jeon;Byeongcheon Lee;Subeen Leem;Jihoon Moon
    • Annual Conference of KIPS
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    • 2023.05a
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    • pp.748-750
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    • 2023
  • Facial expression recognition technology's rapid growth and development have garnered significant attention in recent years. This technology holds immense potential for various applications, making it crucial to stay up-to-date with the latest trends and advancements. Simultaneously, it is essential to identify and address the challenges that impede the technology's progress. Motivated by these factors, this study aims to understand the latest trends, future directions, and challenges in facial expression recognition technology by utilizing text mining to analyze papers published between 2020 and 2023. Our research focuses on discerning which aspects of these papers provide valuable insights into the field's recent developments and issues. By doing so, we aim to present the information in an accessible and engaging manner for readers, enabling them to understand the current state and future potential of facial expression recognition technology. Ultimately, our study seeks to contribute to the ongoing dialogue and facilitate further advancements in this rapidly evolving field.

A Comparative Study on the Types and its Importance of Trade Claims between China and the United States: Using Text Mining Techniques (중국과 미국의 무역클레임 유형과 중요도 비교 연구 : 텍스트 마이닝 기법을 활용하여)

  • Cheon Yu;Yun-Seop Hwang
    • Korea Trade Review
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    • v.47 no.3
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    • pp.177-190
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    • 2022
  • This study is designed to identify the differences in the types and importance of trade claims at the national level. For analysis data, abstracts of arbitration and court judgments published on the website of the United Nations Commission on International Trade Law are collected and used. The target countries are China and the United States, with 102 cases from China and 59 cases from the United States. By applying topic modeling techniques to the collection decisions of China and the United States, trade claims are categorized, and the importance of each type is identified using the network centrality index derived through semantic network analysis. The analysis results are as follows. First, the main types of trade claims were the same for both the United States and China: product nonconformity, delivery issues, and payments. However, in China, the order of product nonconformity > delivery issues > payments was important, and in the United States, payments > product nonconformity > delivery issues were found to be important. This study is significant in that it presents a strategic trade claim management plan using a quantitative methodology.

Network, Centrality, and Topic Analysis on Korea's Trade and Economy with Latin America and the Caribbean Area (한국의 중남미 지역연구 네트워크와 중심성 및 무역과 경제에 대한 토픽 변동분석)

  • Chae-Deug Yi
    • Korea Trade Review
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    • v.47 no.6
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    • pp.189-209
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    • 2022
  • This study aims to analyze Latin America and the Caribbean papers published in Korea during the past 2000-2020 years. Through this study, it is possible to understand the main subject and direction of research in Korea's Latin America and the Caribbean area. As the research mythologies, this study uses the text mining and Social Network Analysis such as frequency analysis, several centrality analyses, and topic analysis. After analyzing the empirical results, there has been a tendency to change the key words and centrality coefficients between 2000-2010 and 2011-2020 years. During 2011-2020 years, the most frequent keywords were changed from Neoliberalism and culture to policy education, and economy related words. The degree and closeness centrality analyses appeared the higher frequency key words. However, the eigenvector centrality appeared very different from the order of frequency key words. The topic analysis shows that the culture, language, and Neoliberalism were the most important keywords during 2000-2010 years but economy, labor trade, industry, development became the most important keywords during 2011-2020 years in topics.

A Study on the Failure Experiences of Online Fashion Shopping Mall Startups -Applying Text Mining and Grounded Theory- (온라인 패션 쇼핑몰 창업의 실패 경험에 관한 연구 -텍스트 마이닝과 근거이론을 적용하여-)

  • Min Jeong Seo
    • Journal of the Korean Society of Clothing and Textiles
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    • v.47 no.6
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    • pp.1096-1112
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    • 2023
  • Many entrepreneurs who launched online fashion shopping malls faced failure compared to those who achieved success. Recognizing the importance of research that reflects reality, this study explores entrepreneurs' experiences during the failure process of online fashion shopping malls. Two studies utilized YouTube videos documenting such online fashion shopping malls' failure. Study 1 employed text mining techniques, including high-frequency analysis and topic modeling, while Study 2 used a qualitative research method, specifically grounded theory. Study 1 identified the prominent experiences of operating online fashion shopping malls, while Study 2 provided a holistic perspective on the failure processes. The integrated findings from both studies highlight that entrepreneurs' passion for fashion motivates them to establish online fashion shopping malls, yet they encounter numerous challenges during the operational process. Insufficient business preparation and operational capabilities contribute to their failure to achieve financial goals. Despite efforts to boost sales and profit, entrepreneurs often close their businesses due to inadequate funds and waning motivation. The outcomes of this study can inform us about the operational challenges faced by online fashion shopping malls and offer valuable insights for developing new strategies to sustain and improve them.

A Study on Perceptions of Virtual Influencers through YouTube Comments -Focusing on Positive and Negative Emotional Responses Toward Character Design- (유튜브 댓글을 통해 살펴본 버추얼 인플루언서에 대한 인식 연구 -캐릭터 디자인에 대한 긍부정 감성 반응을 중심으로-)

  • Hyosun An;Jiyoung Kim
    • Journal of the Korean Society of Clothing and Textiles
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    • v.47 no.5
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    • pp.873-890
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    • 2023
  • This study analyzed users' emotional responses to VI character design through YouTube comments. The researchers applied text-mining to analyze 116,375 comments, focusing on terms related to character design and characteristics of VI. Using the BERT model in sentiment analysis, we classified comments into extremely negative, negative, neutral, positive, or extremely positive sentiments. Next, we conducted a co-occurrence frequency analysis on comments with extremely negative and extremely positive responses to examine the semantic relationships between character design and emotional characteristic terms. We also performed a content analysis of comments about Miquela and Shudu to analyze the perception differences regarding the two character designs. The results indicate that form elements (e.g., voice, face, and skin) and behavioral elements (e.g., speaking, interviewing, and reacting) are vital in eliciting users' emotional responses. Notably, in the negative responses, users focused on the humanization aspect of voice and the authenticity aspect of behavior in speaking, interviewing, and reacting. Furthermore, we found differences in the character design elements and characteristics that users expect based on the VI's field of activity. As a result, this study suggests applications to character design to accommodate these variations.

Exploring Subcultural Capital in Sneakerhead Culture -A Netnographic Investigation- (스니커헤드 하위문화에 대한 네트노그라피 분석 -하위문화자본 개념을 중심으로-)

  • Solhwi Kim;Eunhyuk Yim
    • Journal of the Korean Society of Clothing and Textiles
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    • v.47 no.5
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    • pp.943-958
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    • 2023
  • This study explores the sneakerhead subculture through the lens of subcultural capital, primarily focusing on online community interactions. The analysis utilizes text mining techniques and netnographic research methods to examine textual data extracted from the online sneakerhead community and aims to elucidate manifestations of subcultural capital within the subculture. The findings underscore several key points: Firstly, shared experiences cultivated by the collective consciousness of subcultural capital foster solidarity among members. Secondly, ongoing validation of authenticity and comprehension of sneakers' cultural significance are member requirements. Subsequently, exhibiting greater levels of subcultural capital empowers members, resulting in hierarchical structures both within and beyond the community. Fourthly, resale-driven sneaker commercialization yields positive outcomes, including individual profit and cultural expansion, yet also brings negative consequences, such as market distortion and intra-community conflict. Lastly, the online community fills a pivotal role in dictating subcultural trends, effectively functioning as an institutional network. Given sneakers' enduring status as a fashion phenomenon, further examination of in this realm is warranted.

Visualization of University Curriculum for Multidisciplinary Learning: A Case Study of Yonsei University, South Korea

  • Geonsik Yu;Sunju Park
    • Journal of Information Science Theory and Practice
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    • v.12 no.1
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    • pp.77-86
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    • 2024
  • As the significance of knowledge convergence continues to grow, universities are making efforts to develop methods that promote multidisciplinary learning. To address this educational challenge, our paper applies network theory and text mining techniques to analyze university curricula and introduces a graphical syllabus rendering method. Visualizing the course curriculum provides a macro and structured perspective for individuals seeking alternative educational pathways within the existing system. By visualizing the relationships among courses, students can explore different combinations of courses with comprehensive search support. To illustrate our approach, we conduct a detailed demonstration using the syllabus database of Yonsei University. Through the application of our methods, we create visual course networks that reveal the underlying structure of the university curriculum. Our results yield insights into the interconnectedness of courses across various academic majors at Yonsei University. We present both macro visualizations, covering 18 academic majors, and visualizations for a few selected majors. Our analysis using Yonsei University's database not only showcases the value of our methodology but also serves as a practical example of how our approach can facilitate multidisciplinary learning.

Text Mining-Based Analysis of Customer Reviews in Hong Kong Cinema: Uncovering the Evolution of Audience Preferences (홍콩 영화에 관한 고객 리뷰의 텍스트 마이닝 기반 분석: 관객 선호도의 진화 발견)

  • Huayang Sun;Jung Seung Lee
    • Journal of Information Technology Applications and Management
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    • v.30 no.4
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    • pp.77-86
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    • 2023
  • This study conducted sentiment analysis on Hong Kong cinema from two distinct eras, pre-2000 and post-2000, examining audience preferences by comparing keywords from movie reviews. Before 2000, positive keywords like 'actors,' 'performance,' and 'atmosphere' revealed the importance of actors' popularity and their performances, while negative keywords such as 'forced' and 'violence' pointed out narrative issues. In contrast, post-2000 cinema emphasized keywords like 'scale,' 'drama,' and 'Yang Yang,' highlighting production scale and engaging narratives as key factors. Negative keywords included 'story,' 'cheesy,' 'acting,' and 'budget,' indicating challenges in storytelling and content quality. Word2Vec analysis further highlighted differences in acting quality and emotional engagement. Pre-2000 cinema focused on 'elegance' and 'excellence' in acting, while post-2000 cinema leaned towards 'tediousness' and 'awkwardness.' In summary, this research underscores the importance of actors, storytelling, and audience empathy in Hong Kong cinema's success. The industry has evolved, with a shift from actors to production quality. These findings have implications for the broader Chinese film industry, emphasizing the need for engaging narratives and quality acting to thrive in evolving cinematic landscapes.

Patent Trend Analysis of Unmanned Ground Vehicles(UGV) using Topic Modeling (토픽모델링을 이용한 무인지상차량(UGV) 특허 동향 분석)

  • Kihwan Kim;Chasoo Jun;Chiehoon Song;Jeonghwan Jeon
    • Journal of the Korea Institute of Military Science and Technology
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    • v.27 no.3
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    • pp.395-405
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    • 2024
  • This study provides a thorough examination of Unmanned Ground Vehicles(UGVs), focusing on crucial technologies and trends across major global markets. It includes an in-depth patent analysis revealing the dominant positions of the United States and the European Union in this field. Additionally, it underscores substantial advancements made by China, Japan, and Korea since 2010. Using Latent Dirichlet Allocation(LDA)-based patent text mining, the study identified key technology areas in UGV development, such as advanced control systems, navigation technologies, power supply mechanisms, and sensing and communication tools. Through linear regression analysis, the study predicted the future paths of these technology areas, offering important insights into the evolving world of UGV technology. The findings can provide strategic guidance for stakeholders in the defense, commercial, and academic sectors, pointing out the future directions in UGV advancements.

Exploring the Factors Influencing the Adaptation of Novice Nutrition Teachers Using Big Data Analysis (빅데이터 분석을 활용한 저경력 영양교사에 대한 교직 적응 요인 연구)

  • Yunsil Kim;Seieun Kim;Hak-Seon Kim;Sunny Ham
    • Journal of the Korean Dietetic Association
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    • v.30 no.4
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    • pp.227-239
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    • 2024
  • This study aimed to analyze the factors influencing the adaptation of novice nutrition teachers through big data analysis and to propose strategies for enhancing this process. Data were collected from internet portals using the keywords 'novice nutrition teacher' and 'nutrition teacher' from May 25, 2021, to May 25, 2024. Text mining techniques, including frequency analysis, semantic network analysis, and CONvergence of iterated CORrelations (CONCOR) analysis, were employed. Key terms such as 'teacher', 'nutrition', 'career', 'school', and 'school meals' exhibited high frequency and centrality, indicating the multifaceted roles of novice nutrition teachers and the need for increased support. Excessive workload and stress related to school meal management negatively impacted adaptation, highlighting the need for systematic management and capacity-building training programs. Mentoring and consulting systems played a crucial role in enhancing professional development, leading to better adaptation and higher job satisfaction. Additionally, stress and anxiety during the appointment preparation process were significant factors influencing adaptation, suggesting the need for improvements in the training curriculum at teacher education institutions. These findings provide valuable insights for developing policies to support the adaptation of novice nutrition teachers.