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structural topic model-based comparative review of human pose estimation research in the United States and China

MULTIMEDIA TOOLS AND APPLICATIONS 2023年第20期83卷 59379-59412页

作者： Sheng, Bo Chen, Xiaohui Zhang, Yanxin Tao, Jing Sun, Yueli Shanghai Univ Sch Mechatron Engn & Automat 99 Shangda Rd Shanghai 200444 Peoples R China Shanghai Univ Shanghai Key Lab Intelligent Mfg & Robot 99 Shangda Rd Shanghai Peoples R China Univ Auckland Dept Exercise Sci 4703906 Newmarket Auckland New Zealand Shanghai Univ TCM Longhua Hosp 725 South Wanping Rd Shanghai 200032 Peoples R China

Human pose estimation, a key area in computer vision, benefits various fields. The comparative study of research approaches in the United States and China, both leaders in this domain, is vital for understanding and influencing global trends in this technology. This review collected 191 influential papers from 2014 to 2022, sourced from Google Scholar. The structural topic model (STM) was utilized to analyze research content, preferences, and trends in research topics. Specifically, 10 topics were summarized, and topic proportions, preferences, intensities, and word clouds were displayed via visualization methods. The findings revealed: 1) research on feature extraction and depth image constituted the largest proportion, approximately 12.2%, while data training research accounted for the lowest proportion, around 7.9%;2) the United States and China exhibited distinct research preferences: the United States focused more on model and data research, while China emphasized deep learning and neural networks;3) both countries exhibited similar research trends within the same topics, and research on deep learning technologies has experienced a slowdown in recent years. By comparative study, this review offers valuable insights and guidance for future investigations and applications in human pose estimation, such as improving the quality and diversity of data sets.

关键词： Human pose estimation structural topic model Comparative review Deep learning Computer vision

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Exploring Debugging Challenges and Strategies Using structural topic model: A Comparative Analysis of High and Low-Performing Students

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JOURNAL OF EDUCATIONAL COMPUTING RESEARCH 2025年第8期62卷 2104-2126页

作者： Park, Eunsung Cheon, Jongpil Tennessee Technol Univ Cookeville TN USA Texas Tech Univ Lubbock TX 79409 USA

Debugging is essential for identifying and rectifying errors in programming, yet time constraints and students' trivialization of errors often hinder progress. This study examines differences in debugging challenges and strategies among students with varying computational thinking (CT) competencies using weekly coding journals from an online undergraduate CT course. Participants used Scratch, a block-based programming language, and their journals from five assignments were analyzed using Term Frequency-Inverse Document Frequency and structural topic modeling. High-performing students engaged with diverse topics and specific blocks tied to their weekly projects while low-performing students faced repetitive and broad challenges, such as understanding motion blocks and broadcast concepts. These patterns reveal that low-performing students struggle particularly during the 'diagnose the fault' phase of debugging, often hindering their progress in the final stage. Such challenges highlight the necessity for targeted educational interventions to improve the debugging proficiency and overall CT skills. The study underscores the importance of further research into students' logical thinking processes during code review and debugging, suggesting the use of think-aloud protocols and detailed tracking of debugging practices for deeper insights. This research contributes to the field by showing that differentiated instruction and strategic support can enhance debugging skills across different student performance levels.

关键词： computational thinking debugging strategies debugging challenges block-based programming structural topic model

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Airbnb customer experience in long-term stays: a structural topic model and ChatGPT-driven analysis of the reviews of remote workers

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INTERNATIONAL JOURNAL OF CONTEMPORARY HOSPITALITY MANAGEMENT 2025年第1期37卷 161-179页

作者： Ramos-Henriquez, Jose M. Morini-Marrero, Sandra Univ La Laguna Fac Econ Business & Tourism Dept Business Management & Econ Hist San Cristobal De La Lagun Spain Univ La Laguna Inst Univ Empresa IUDE San Cristobal la Laguna Spain Univ La Laguna Fac Econ Business & Tourism Dept Accounting & Financial Econ San Cristobal De La Lagun Spain

PurposeThis study aims to characterize remote workers' Airbnb experiences through the cognitive outcomes of their experiences and to consider the differences between long and short ***/methodology/approachThe structural topic model methodology was used to identify relevant topics. Data were collected from InsideAirbnb for Lisbon, Portugal and Austin, Texas, USA, for 2022 and early 2023, focusing on reviews that mentioned remote *** Airbnb experiences of remote workers and digital nomads are characterized as professionals who express mostly affective outcomes, but also have behavioral and nonaffective outcomes during their stay. In addition, the findings support the moderating role of length of stay and *** limitations/implicationsThis paper contributes to the literature by exploring how length of stay affects the priorities of remote workers on Airbnb, highlighting the different needs of long-term and short-term stays, and helping to consolidate and clarify the scattered research on customers' long-term experiences in tourism and *** implicationsThe Airbnb experience of remote workers is the highly valued as evidenced by the high rate of commending reviews indicating a willingness to stay there again. It is suggested that Airbnb hosts continue their helpful role and ensuring the functionality and availability of essential facilities and emphasizing neighborhood amenities specific to long and short stays. ChatGPT4 was found to be valuable for extracting data and assigning topic ***/valueThis study uses a novel structural topic model, augmented with ChatGPT4, to analyze Airbnb customer reviews that mention remote work, thereby improving inferences about the characterization of remote workers.

关键词： Long-term stays Remote workers Digital nomads structural topic model ChatGPT Airbnb customer experience

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Central Asian studies in the People's Republic of China: a structural topic model

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CENTRAL ASIAN SURVEY 2024年第3期43卷 307-326页

作者： Maracchione, Frank Jardine, Bradley Univ Sheffield Sheffield England Wilson Ctr Washington DC USA Oxus Soc Cent Asian Affairs Washington DC USA

China has a rich Central Asia studies literature and in recent years, it has seen an expansion in the number of research institutions with a regional focus. We apply a structural topic model, a quantitative method that estimates thematic prevalence through machine learning, to analyse publications on Central Asia in Chinese academic and specialist journals to show how the field has evolved over time. Aside from the methodological contribution we offer an original dataset of 10,563 publications scraped from China's CNKI database. We test our strategy on two assumptions in Western literature on Chinese academics' understanding of Central Asia: (1) China's research institutes are primarily concerned with economics and (2) China's thinking on strategic regions is lacking in local context, unique cultural concepts and insights. We argue that while China's scholarship on the region is often Sinocentric, some research shows diversity and nuance, with more analytical depth that has been traditionally understood.

关键词： China Chinese academia Central Asia knowledge production area studies structural topic model

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The identity-attitude nexus in the representation of energy transition in a coal region (Sulcis, Italy): An exploration through the structural topic model

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EUROPEAN JOURNAL OF SOCIAL PSYCHOLOGY 2024年第1期54卷 118-135页

作者： Rizzoli, Valentina Biddau, Fulvio Sarrica, Mauro Sapienza Univ Rome Dept Commun & Social Res ViaSalaria 113 I-00198 Rome Italy Univ Padua Dept Philosophy Sociol Educ & Appl Psychol Padua Italy Euro Mediterranean Ctr Climate Change Bologna Italy

This article explores the contribution of the structural topic model (STM) to study the intertwining of social representations, attitudes, and identities. We examine newspapers' discourse on energy transition in a coal-dependent region (Sulcis, Italy), whose identity and economy are built around mining and carbon-intensive industry. Drawing upon Social Representations Theory, we combined STM and qualitative content analysis to examine how newspapers represented the energy issue in Sulcis, and how these representations (including denotative and connotative facets) differed according to the social identities' salience. Results show that coal is legitimated by discourses making salient local identities and providing continuity in the place-identity link, with no alternative to extractivism. When the Sardinian superordinate identity becomes salient, new themes emerge (e.g., renewables) but energy transition retains ambivalent or negative connotations. Overall representations seem to replicate and reflect processes of domination and injustice hindering a just transition, potentially explaining negative attitudes and collective resistance to decarbonization.

关键词： attitude energy transition identity natural language processing social representations structural topic model

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A structural topic model for Exploring User Satisfaction with Mobile Payments

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Computers, Materials & Continua 2022年第11期73卷 3815-3826页

作者： Jang Hyun Kim Jisung Jang Yonghwan Kim Dongyan Nan Department of Human-Artificial Intelligence Interaction Sungkyunkwan UniversitySeoul03063Korea Department of Interaction Science Sungkyunkwan UniversitySeoul03063Korea Department of Applied Artificial Intelligence Sungkyunkwan UniversitySeoul03063Korea NAVER Green Factory Seongnam13561Korea

This study explored user satisfaction with mobile payments by applying a novel structural topic ***,we collected 17,927 online reviews of a specific mobile payment(i.e.,PayPal).Then,we employed a structural topic model to investigate the relationship between the attributes extracted from online reviews and user satisfaction with mobile ***,we discovered that“lack of reliability”and“poor customer service”tend to appear in negative ***,the terms“convenience,”“user-friendly interface,”“simple process,”and“secure system”tend to appear in positive *** the basis of information system success theory,we categorized the topics“convenience,”“user-friendly interface,”and“simple process,”as system *** addition,“poor customer service”was categorized as service ***,based on the previous studies of trust and security,“lack of reliability”and“secure system”were categorized as trust and security,*** outcomes indicate that users are satisfied when they perceive that system quality and security of specific mobile payments are *** the contrary,users are dissatisfied when they feel that service quality and reliability of specific mobile payments is ***,our research implies that a novel structural topic model is an effective method to explore mobile payment user experience.

关键词： Mobile payment user satisfaction online review structural topic model

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Different voices between Airbnb and hotel customers: An integrated analysis of online reviews using structural topic model

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JOURNAL OF HOSPITALITY AND TOURISM MANAGEMENT 2022年 51卷 119-131页

作者： Gao, Baojun Zhu, Minyue Liu, Shan Jiang, Mei Wuhan Univ Econ & Management Sch Wuhan 430072 Peoples R China Xi An Jiao Tong Univ Sch Management Xian 710049 Peoples R China

Understanding customer preferences is important for Airbnb accommodation hosts and hotel managers because they compete with and complement each other. As such, this study investigates the topics that appear in Airbnb reviews more than in hotel reviews, the associated sentiment orientation, and how each topic changes with the price and rating of properties. Analysis of 33,487 Airbnb and TripAdvisor reviews using the structural topic model show that out of the 23 topics documented in Airbnb literature, only 12 topics appear more in Airbnb reviews than in hotel reviews. We find that topics of Recommend, Host, Location and Feeling at home associate with positive sentiment, while topics on Smell, Cleanliness, Amenities and In-room facilities tend to be negative. Moreover, friendly host-customer interaction and homey atmosphere determine the highly-rated Airbnb listings, while pleasurable communication with hosts, convenient location, and reliable amenities are the features of high-priced Airbnb listings. These findings enhance our understanding of the preferences and service perceptions of Airbnb customers.

关键词： Airbnb Online review structural topic model Hotel Sentiment analysis

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Research topics and trends in the maritime transport: A structural topic model

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TRANSPORT POLICY 2021年 102卷 11-24页

作者： Bai, Xiwen Zhang, Xiunian Li, Kevin X. Zhou, Yaoming Yuen, Kum Fai Tsinghua Univ Dept Ind Engn Beijing Peoples R China Traveloka Technol Singapore Singapore Zhejiang Univ Ocean Coll Zhoushan Peoples R China Shanghai Jiao Tong Univ Dept Ind Engn & Management Shanghai Peoples R China Nanyang Technol Univ Sch Civil & Environm Engn Singapore Singapore

Maritime transport is considered as the lynchpin of global trade. In the past decades, a large number of academic articles in the maritime transport field have been published. This study aims to provide a comprehensive review of the development of maritime transport research. A structural topic model (STM) is adopted to analyze the research themes and trends in the maritime literature. STM is a text mining-based methodology to uncover main topics from large-scale unstructured textual data. In total, 3199 articles published between Jan 1991 and Aug 2020 were collected and analyzed. The results show that the major academic concerns of maritime transport are related to port management, container operations and liner shipping management. The overall research trends have shifted from regulations and policy management to efficient, integrated and sustainable maritime transport over the past few decades. The main research topics and emerging trends discovered from STM can facilitate researchers, funding groups and policymakers for identifying contemporary research issues and making more informed decisions.

关键词： Maritime transport Shipping Port Text mining structural topic model Research trends

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Delineating development trends of nanotechnology in the semiconductor industry: Focusing on the relationship between science and technology by employing structural topic model

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TECHNOLOGY IN SOCIETY 2023年第1期74卷

作者： Kang, Inje Yang, Jiseong Lee, Wonjae Seo, Eun-Yeong Lee, Duk Hee Korea Adv Inst Sci & Technol Coll Business Sch Business & Technol Management 291 Daehak Ro Daejeon South Korea Korea Adv Inst Sci & Technol Grad Sch Culture Technol 291 Daehak Ro Daejeon South Korea Samsung SDS Consulting Team 125 Olymp Ro35 Gil Seoul South Korea Korea Adv Inst Sci & Technol Sch Business & Technol Management Bldg N22291 Daehak Ro Daejeon 34141 South Korea

The bibliometrics research on nanotechnology highlights close interrelationships between scientific and technological activities (S & T) in the field of nanotechnology. Notwithstanding abundant empirical evidence on the mutual relations between S & T, the dynamics of the relationship from a contextual perspective have gained relatively little attention. Accordingly, our understanding of how science- and technology-oriented nanotechnology identifies development opportunities from each other is still at a nascent stage. To address this gap, by focusing on nanotechnology in the semiconductor industry, we use structural topic model to empirically explore the dynamic interrelationships between science- and technology-oriented nanotechnology. We empirically delineate the dynamic development trends in the context of the interrelationships between S & T and demonstrate how development opportunities are identified from each other. These findings show a new window of opportunities for how state-of-the-art models for semantic analysis can be used in the literature on S & T interrelationships.

关键词： Nanotechnology Science-oriented nanotechnology Technology-oriented nanotechnology S & amp T interrelationships Development opportunities structural topic model

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Investigating emerging hydrogen technology topics and comparing national level technological focus: Patent analysis using a structural topic model

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APPLIED ENERGY 2022年 313卷

作者： Choi, Hyunhong Woo, JongRoul Kyung Hee Univ Dept Ind & Management Syst Engn 1732 Deogyeong Daero Yongin 17104 Gyeonggi South Korea Korea Univ Grad Sch Energy & Environm KU KIST Green Sch Energy Environm Policy & Technol 145 Anam Ro Seoul 02841 South Korea

Hydrogen technology has recently attracted great attention as a new energy technology with a potential to transform existing energy systems. However, since hydrogen technology is based on a concept encompassing a broad range of topics, such as hydrogen production, storage, distribution, and utilization, it is difficult for individual field experts to analyze it from an integrated viewpoint. In this study, we used a semiautomated, unsupervised learning approach for patent data analysis to identify specific technology topics in various fields of hydrogen technology and to analyze the technological focus of key countries. Thus, we collected 17 281 hydrogen technology patents from the last decade (2010-2019) from the United States Patent and Trademark Office (USPTO) and input the text in the title and abstract of the collected patents along with their metadata to a structural topic model. Consequently, we identified various hydrogen technology topics estimated based on the co-occurrence pattern of words within patents and represented as probabilistic word distribution. Furthermore, the metadata of the collected patents were used to identify topics that were newer or more impactful and appeared more frequently in patents from a certain country. After identifying technology topics, we also estimated the technology maturity rate (TMR) of each topic to measure its remaining potential. Among the 40 latent technology topics identified from the collected patents, 11 topics showed increasing proportion over time (new and trending) and five topics were highly cited by other patents (impactful). Furthermore, based on the analysis results, implications were presented for hydrogen research and development (R&D) strategy by (1) comparing the technology portfolios of key countries, (2) performing a technology correlation analysis of the identified hydrogen technology topics, and (3) proposing a decision framework for policymakers to categorize identified topics. We found that the pri

关键词： Hydrogen technology Research and development strategy structural topic model Patent analysis

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