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Interdisciplinary integration and development trends of intelligent diagnosis in traditional Chinese medicine:a topic evolution analysis 认领 引用 被引量：1
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作者 Chenggong Xie Keying Huang +2 位作者 Zhengquan Du Xinyi Huang Bin Wang 《Digital Chinese Medicine》 CAS CSCD 2026年第1期43-56,共14页
Objective To systematically characterize the developmental trajectory and interdisciplinary integration of intelligent diagnosis in traditional Chinese medicine(TCM)through quantitative topic evolution analysis,we add... Objective To systematically characterize the developmental trajectory and interdisciplinary integration of intelligent diagnosis in traditional Chinese medicine(TCM)through quantitative topic evolution analysis,we addressed the fragmentation of existing research and clarified the long-term research structure and evolutionary patterns of the field.Methods A topic evolution analysis was performed on Chinese-language literature pertaining to intelligent diagnosis in TCM.Publications were retrieved from the China National Knowledge Infrastructure(CNKI),Wanfang Data,and China Science and Technology Journal Database(VIP),covering the period from database inception to July 3,2025.A hybrid segmentation approach,based on cumulative publication growth trends and inflection point detection,was applied to divide the research timeline into distinct stages.Subsequently,the latent Dirichlet allocation(LDA)model was used to extract research topics,followed by alignment and evolutionary analysis of topics across different stages.Results A total of 3919 publications published between 2003 and 2025 were included,and the research trajectory was divided into five stages based on data-driven breakpoint detection.The field exhibited a clear evolutionary shift from early rule-based systems and tonguepulse image and signal analysis(2006–2010),to machine-learning-based syndrome and prescription modeling(2011–2015),followed by deep-learning-driven pattern recognition and formula association(2016–2020).Since 2021,research has increasingly emphasized knowledge-graph construction,multimodal integration,and intelligent clinical decision-support systems,with recent studies(2024–2025)showing the emergence of large language models and agent-based diagnostic frameworks.Topic evolution analysis further revealed sustained cross-stage continuity in syndrome modeling and prescription association analysis,alongside the progressive consolidation of integrated intelligent diagnostic platforms.Conclusion By identifying key technological transitions and persistent core research themes,our findings offer a structured reference framework for the design of intelligent diagnostic systems,the construction of knowledge-driven clinical decision-support tools,and the alignment of AI models with TCM diagnostic logic.Importantly,the stage-based evolutionary insights derived from this analysis can inform future methodological choices,improve model interpretability and clinical applicability,and support the translation of intelligent TCM diagnosis from experimental research to real-world clinical practice. 展开更多
关键词 Traditional Chinese medicine diagnosis Artificial intelligence Interdisciplinary integration Research stage identification Topic evolution analysis Latent Dirichlet allocation model
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Mapping editorial identity and thematic evolution in the Journal of Psychology in Africa(2008-2024):A meta-editorial framework analysis 认领 引用
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作者 Joon-ho Kim 《Journal of Psychology in Africa》 2026年第1期117-130,共14页
This study presents a reflective bibliometric review of 1457 peer-reviewed articles published in the Journal of Psychology in Africa(2008-2024,17 years),using a Meta-Editorial Mapping Framework(MEMF)analysis.The MEMF ... This study presents a reflective bibliometric review of 1457 peer-reviewed articles published in the Journal of Psychology in Africa(2008-2024,17 years),using a Meta-Editorial Mapping Framework(MEMF)analysis.The MEMF integrates citation metrics,keyword novelty ratios,TF-IDF weighting,and cluster-based topic modeling to trace long-term thematic trends and editorial evolution.Findings reveal sustained attention to foundational domains such as mental health,education,and identity,alongside a gradual integration of emergent themes including digital well-being,organizational behavior,and post-pandemic adaptation.Articles with moderate topical novelty(40%-60% new keywords)achieved the highest citation and usage metrics,suggesting that integrative innovation enhances scholarly impact.Clustering analyses indicate that the journal’s content forms overlapping conceptual domains rather than isolated silos.These insights contribute to editorial strategy,authorial positioning,and the future design of regional academic platforms.Moreover,the findings provide evidence supporting the use of the MEMF as a replicable tool for meta-editorial analysis across disciplinary and geographic boundaries. 展开更多
关键词 meta-editorial mapping framework(MEMF) topic evolution keyword novelty bibliometric analysis editorial strategy scholarly engagement Journal of Psychology in Africa
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Evolution and insights of China’s environmental governance policies:An LDA-based policy text analysis 认领 引用
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作者 HUA Yu-chen YANG Jia-meng +2 位作者 WEI Ren-jie CHENG Xiu LIU Zhi-yong 《Ecological Economy》 2026年第1期2-30,共29页
China’s environmental governance strategy provides a distinctive pathway for integrating sustainable development into national policy.Understanding its policy trajectory is essential for assessing China’s contributi... China’s environmental governance strategy provides a distinctive pathway for integrating sustainable development into national policy.Understanding its policy trajectory is essential for assessing China’s contribution to global sustainable development and the United Nations Sustainable Development Goals(SDGs).This study constructs a comprehensive database of 425 national environmental governance policy documents issued between 1978 and 2022 and applies Latent Dirichlet Allocation(LDA)modeling to examine the evolution of policy themes and discourse.The results show that China’s environmental governance has undergone four stages-initial exploration,detailed development,transformative leap,and diverse prosperity-reflecting a progressive shift toward more integrated and coordinated governance.Policy priorities have evolved from a primary focus on pollution control and energy transition to an emphasis on institutional construction and organizational reform,thereby strengthening alignment with the SDGs.This transformation is characterized by recurring developmental themes and increasingly preventive,forward-looking,and system-oriented governance approaches.Moreover,the co-evolution of policy concepts and implementation has driven a transition from localized,end-of-pipe responses to comprehensive governance frameworks,alongside a shift from normative guidance towards effectiveness-oriented policy design.By employing a data-driven text analysis approach,this study offers a systematic framework for tracing long-term policy evolution and assessing its implications for sustainable development. 展开更多
关键词 environmental governance policy text analysis LDA topic modeling topic evolution sustainable development policy policy transformation
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Topic Mining and Evolution Analysis of Domestic Smart Library Research Based on the BERTopic Model 认领 引用
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作者 Meile Li Yinuo Jiang 《Journal on Artificial Intelligence》 2025年第1期509-516,共8页
This paper conducts topic mining and analysis of research literature in the domestic smart library field based on the BERTopic model,aiming to reveal its topic development context and evolution trends.Journal literatu... This paper conducts topic mining and analysis of research literature in the domestic smart library field based on the BERTopic model,aiming to reveal its topic development context and evolution trends.Journal literature in the smart library field collected by CNKI(China National Knowledge Infrastructure)from 2015 to 2024 was analyzed using the BERTopic model and dynamic topic modeling for topic mining and evolution trend analysis.The study found that the domestic smart library field involves multiple core topics,identifying a diversified topic structure centered around“data”,“user”,“5g”,etc.The research results provide data support and practical reference for libraries to accurately identify key points of technology integration during smart transformation and to optimize smart service models. 展开更多
关键词 Domestic smart library BERTopic topic mining evolution analysis
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The power of ChatGPT in processing text:Evidence from analysis and prediction in the exchange rate markets 认领 引用
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作者 Kun Yang Ruxin Deng +1 位作者 Yunjie Wei Shouyang Wang 《Financial Innovation》 2025年第1期3419-3451,共33页
This study investigates the application of large language models in analyzing sentiment features within the exchange rate markets.Traditional natural language processing methods,such as LDA and BERT,are effective in e... This study investigates the application of large language models in analyzing sentiment features within the exchange rate markets.Traditional natural language processing methods,such as LDA and BERT,are effective in extracting topics from text;however,they fail to assess the relative importance of these topics in relation to target exchange rates.To bridge this gap,this paper employs ChatGPT to extract topics from texts and evaluate their importance scores,further enhancing exchange rate forecasting by integrating topic importance into the sentiment analysis framework.Through empirical analysis,the superiority of ChatGPT over LDA and BERT in both topic extraction and importance assessment is demonstrated.Furthermore,this study utilizes the topic importance scores generated by ChatGPT to develop a novel interval-valued sentiment index(TIS index).This index not only accounts for the relative importance of various events influencing exchange rate fluctuations but also captures the dynamic evolution of market sentiment within an interval.Empirical results highlight that the TIS Index significantly enhances the forecasting accuracy of interval models such as TARI and IMLP for exchange rates.These findings further demonstrate the advantages of ChatGPT in sentiment analysis within the foreign exchange market.These findings offer new insights into the application of ChatGPT in financial text research. 展开更多
关键词 ChatGPT Sentiment analysis Exchange rate Topic analysis Interval
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基于TopicGPT模型的智慧养老研究主题挖掘与演化分析 认领 引用 被引量：2
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作者 曾鹏翔 刘天畅 +1 位作者 蒲政同 朱庆华 《情报科学》 CSSCI 北大核心 2026年第2期91-102,共12页
【目的/意义】针对人口老龄化加速与生成式人工智能技术变革背景下,传统智慧养老服务研究存在的碎片化问题与方法局限性,本研究融合生成式人工智能与深度学习技术构建TopicGPT新型主题模型,系统性分析智慧养老领域的研究动态,为“AI+养... 【目的/意义】针对人口老龄化加速与生成式人工智能技术变革背景下,传统智慧养老服务研究存在的碎片化问题与方法局限性,本研究融合生成式人工智能与深度学习技术构建TopicGPT新型主题模型,系统性分析智慧养老领域的研究动态,为“AI+养老”范式创新与政策实施提供理论支撑。【方法/过程】基于中国知网2015—2024年智慧养老领域期刊文献,提出TopicGPT混合主题模型框架:通过SBERT词嵌入与UMAP-HDBSCAN聚类实现语义表征,结合Llama2大语言模型优化主题标签生成,最终从4362篇文献中识别40个研究主题,并基于动态主题建模分析其演化路径。【结果/结论】智慧养老研究呈现多维度交叉特征,核心方向包括适老化智能产品设计、数据驱动的智慧养老服务、数字鸿沟治理等。主题演化分析表明,传统主题(如经济效益分析)关注度趋缓,而生成式人工智能、沉浸式虚拟现实等新兴技术驱动的主题(如虚拟养老社区、智能照护系统)呈现显著增长趋势。此外,老年人数字鸿沟、隐私保护等社会性问题持续升温,凸显技术赋能与伦理治理并重的必要性。【创新/局限】运用TopicGPT模型展示了我国智慧养老领域的整体发展态势,突破传统主题模型在语义解析与跨学科整合上的局限,实现细粒度动态演化分析;未来将深化多源数据融合,优化模型模块组合,拓展技术应用场景的实证研究。 展开更多
关键词 智慧养老 生成式人工智能 TopicGPT 主题挖掘 演化分析
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Topic Modelling and Sentimental Analysis of Students’Reviews 认领 引用
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作者 Omer S.Alkhnbashi Rasheed Mohammad Nassr 《Computers, Materials & Continua》 SCIE EI 2023年第3期6835-6848,共14页
Globally,educational institutions have reported a dramatic shift to online learning in an effort to contain the COVID-19 pandemic.The fundamental concern has been the continuance of education.As a result,several novel... Globally,educational institutions have reported a dramatic shift to online learning in an effort to contain the COVID-19 pandemic.The fundamental concern has been the continuance of education.As a result,several novel solutions have been developed to address technical and pedagogical issues.However,these were not the only difficulties that students faced.The implemented solutions involved the operation of the educational process with less regard for students’changing circumstances,which obliged them to study from home.Students should be asked to provide a full list of their concerns.As a result,student reflections,including those from Saudi Arabia,have been analysed to identify obstacles encountered during the COVID-19 pandemic.However,most of the analyses relied on closed-ended questions,which limited student involvement.To delve into students’responses,this study used open-ended questions,a qualitative method(content analysis),a quantitative method(topic modelling),and a sentimental analysis.This study also looked at students’emotional states during and after the COVID-19 pandemic.In terms of determining trends in students’input,the results showed that quantitative and qualitative methods produced similar outcomes.Students had unfavourable sentiments about studying during COVID-19 and positive sentiments about the face-to-face study.Furthermore,topic modelling has revealed that the majority of difficulties are more related to the environment(home)and social life.Students were less accepting of online learning.As a result,it is possible to conclude that face-to-face study still attracts students and provides benefits that online study cannot,such as social interaction and effective eye-to-eye communication. 展开更多
关键词 Topic modelling sentimental analysis COVID-19 students’input
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Building potential patent portfolios: An integrated approach based on topic identification and correlation analysis 认领 引用
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作者 Xian ZHANG Haiyun XU +2 位作者 Shu FANG Zhengyin HU Shuying LI 《Chinese Journal of Library and Information Science》 2015年第2期39-51,共13页
Purpose： This paper suggests a framework to identify important patents for building potential patent portfolios based on patents owned by different assignees so as to highlight the value of individual patents in tech... Purpose： This paper suggests a framework to identify important patents for building potential patent portfolios based on patents owned by different assignees so as to highlight the value of individual patents in technology transfer and identify potential collaborators for patent assignees. Design/methodology/approach： The analysis framework includes the following steps： l） co-classification analysis based on the International Patent Classification （IPC） codes and Derwent Manual Codes （DMC） to detect sub-tech fields, 2） keyword co-occurrence analysis aiming to understand the core technology information in each patent, and 3） social network analysis used for identifying important technologies and partnerships of key assignees. A case study was conducted with 27,401 chemistry patents filed by a Chinese national research institute. Findings： The results show that this framework is effective in building potential technological patent portfolios based on patents owned by different assignees and identifying future collaborators for the assignees. This integrated approach based on topic identification and correlation analysis that combines network-based analysis with keyword-based analysis can reveal important patented technologies and their connections and help understand detailed technological information mentioned in patents. Research limitations： In keywords analysis, only titles and abstracts of patent documents were used and weights of keywords in different parts of the documents were not considered.Practical implications： The analysis framework provides valuable information for decision- makers of large institutions which have many patents with broad application prospects. Originality/value： Different from previous patent portfolio studies based on the use of a combination of patent analysis indicators, this study provides insights into a method of building patent portfolios to discover the potential of individual patents in technology transfer and promote cooperation among different patent assignees. 展开更多
关键词 Patent portfolio Patent cooperation Topic identification Correlation analysis Social network analysis （SNA）
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基于BERTopic模型的企业ESG政策文本主题识别与趋势分析 认领 引用
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作者 孟志华 耿嘉璘 《标准科学》 2026年第3期36-44,共9页
【目的】紧跟时事政策,探究发展趋势,更好地为企业提供参考价值,也为社会公众更整体地了解政策变化。【方法】采用BERTopic模型、数据搜集、文本分析等方法,对近几年各个单位出台的关于企业ESG相关政策进行总结分类和评价,审视主要方向... 【目的】紧跟时事政策,探究发展趋势,更好地为企业提供参考价值,也为社会公众更整体地了解政策变化。【方法】采用BERTopic模型、数据搜集、文本分析等方法,对近几年各个单位出台的关于企业ESG相关政策进行总结分类和评价,审视主要方向并提出不足和建议。【结果】上市公司环境战略、内部环境管理制度、企业信息披露评估框架、绿色债券信息披露、统一国内绿色债券项目认定标准、ESG信息披露的基本架构、定期披露公司信息的义务方面较好,但研究对象存在追责机制不健全、缺少ESG评级质量标准、ESG审计不足的问题。【结论】提出了需要完善追责机制、统一评级质量标准和提升ESG审计水平的建议,最终有效遏制“漂绿”乱象的发生,提升ESG信息质量与公信力,实现长期发展。 展开更多
关键词 ESG BERTopic模型 主题分析 趋势分析
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国内网络谣言治理研究的主题识别与内容分析:基于BERTopic与CiteSpace的对比分析 认领 引用
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作者 刘岩芳 王宇彤 《教育传媒研究》 2026年第2期72-82,共11页
随着人工智能技术的快速发展,网络谣言的生成机制与传播方式日趋复杂,对网络空间治理带来了新的挑战。本文以2015-2024年CNKI数据库收录的1405篇网络谣言治理相关文献为数据来源,运用BERTopic主题建模方法与CiteSpace可视化工具,对该领... 随着人工智能技术的快速发展,网络谣言的生成机制与传播方式日趋复杂,对网络空间治理带来了新的挑战。本文以2015-2024年CNKI数据库收录的1405篇网络谣言治理相关文献为数据来源,运用BERTopic主题建模方法与CiteSpace可视化工具,对该领域研究的阶段演进、关键词分布、热点主题与内容结构等进行对比分析。本研究有助于厘清网络谣言治理领域的知识结构与演化趋势,为推动治理模式优化和提升网络治理效能提供理论参考。 展开更多
关键词 网络谣言治理 BERTopic CiteSpace 主题建模 内容分析
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Topic Sentiment Analysis in Online Learning Community from College Students 认领 引用 被引量：2
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作者 Kai Wang Yu Zhang 《Journal of Data and Information Science》 CSCD 2020年第2期33-61,共29页
Purpose:Opinion mining and sentiment analysis in Online Learning Community can truly reflect the students’learning situation,which provides the necessary theoretical basis for following revision of teaching plans.To ... Purpose:Opinion mining and sentiment analysis in Online Learning Community can truly reflect the students’learning situation,which provides the necessary theoretical basis for following revision of teaching plans.To improve the accuracy of topic-sentiment analysis,a novel model for topic sentiment analysis is proposed that outperforms other state-of-art models.Methodology/approach:We aim at highlighting the identification and visualization of topic sentiment based on learning topic mining and sentiment clustering at various granularitylevels.The proposed method comprised data preprocessing,topic detection,sentiment analysis,and visualization.Findings:The proposed model can effectively perceive students’sentiment tendencies on different topics,which provides powerful practical reference for improving the quality of information services in teaching practice.Research limitations:The model obtains the topic-terminology hybrid matrix and the document-topic hybrid matrix by selecting the real user’s comment information on the basis of LDA topic detection approach,without considering the intensity of students’sentiments and their evolutionary trends.Practical implications:The implication and association rules to visualize the negative sentiment in comments or reviews enable teachers and administrators to access a certain plaint,which can be utilized as a reference for enhancing the accuracy of learning content recommendation,and evaluating the quality of their services.Originality/value:The topic-sentiment analysis model can clarify the hierarchical dependencies between different topics,which lay the foundation for improving the accuracy of teaching content recommendation and optimizing the knowledge coherence of related courses. 展开更多
关键词 Online learning community Topic detection Sentiment analysis
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A Micro Perspective of Research Dynamics Through“Citations of Citations”Topic Analysis 认领 引用 被引量：2
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作者 Xiaoli Chen Tao Han 《Journal of Data and Information Science》 CSCD 2020年第4期19-34,共16页
Purpose:Research dynamics have long been a research interest.It is a macro perspective tool for discovering temporal research trends of a certain discipline or subject.A micro perspective of research dynamics,however,... Purpose:Research dynamics have long been a research interest.It is a macro perspective tool for discovering temporal research trends of a certain discipline or subject.A micro perspective of research dynamics,however,concerning a single researcher or a highly cited paper in terms of their citations and“citations of citations”(forward chaining)remains unexplored.Design/methodology/approach:In this paper,we use a cross-collection topic model to reveal the research dynamics of topic disappearance topic inheritance,and topic innovation in each generation of forward chaining.Findings:For highly cited work,scientific influence exists in indirect citations.Topic modeling can reveal how long this influence exists in forward chaining,as well as its influence.Research limitations:This paper measures scientific influence and indirect scientific influence only if the relevant words or phrases are borrowed or used in direct or indirect citations.Paraphrasing or semantically similar concept may be neglected in this research.Practical implications:This paper demonstrates that a scientific influence exists in indirect citations through its analysis of forward chaining.This can serve as an inspiration on how to adequately evaluate research influence.Originality:The main contributions of this paper are the following three aspects.First,besides research dynamics of topic inheritance and topic innovation,we model topic disappearance by using a cross-collection topic model.Second,we explore the length and character of the research impact through“citations of citations”content analysis.Finally,we analyze the research dynamics of artificial intelligence researcher Geoffrey Hinton’s publications and the topic dynamics of forward chaining. 展开更多
关键词 Research dynamics Forward chaining Topic model Scientific influence Citations content analysis
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Disciplinary Profiles of Local Topics in the Flemish Social Sciences and Humanities 认领 引用
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作者 Cristina Arhiliuc Raf Guns Tim C.E.Engels 《Journal of Data and Information Science》 CSCD 2026年第2期140-153,共14页
Purpose:The study examines how local topics in the Flemish Academic Bibliographic Database for the Social Sciences and Humanities(VABB-SHW)are positioned within a disciplinary framework.It explores their size,language... Purpose:The study examines how local topics in the Flemish Academic Bibliographic Database for the Social Sciences and Humanities(VABB-SHW)are positioned within a disciplinary framework.It explores their size,language profile,and disciplinary profiles compared to the broader topic landscape.Design/methodology/approach:Topics were extracted using the clustering strategy of(Guns,R.2024.“A Bibliometric Map of Local Research in the Social Sciences and Humanities.”In Research Evaluatuion in Social Sciences and Humanities 2024.Galway,Ireland)with BERTopic,combining multilingual embeddings,UMAP dimensionality reduction,and HDBSCAN.Descriptions were generated with GPT-4o-mini,labelled with Gemini-2.5-Flash,and classified with a content-based model trained on Web of Science data and applied to VABB-SHW(Arhiliuc,C.,R.Guns,and T.C.E.Engels.2025b.“Text-Based Classification of all Social Sciences and Humanities Publications Indexed in the Flemish VABB Database.”In Proceedings of the 20th International Conference on Scientometrics&Informetrics(ISSI,2025)).Findings:Out of 517 topics,76(17.2%of publications)were identified as local.They contain more non-English publications,and cluster mainly in“History”,“Law”,“Literature”,“Political science”,and“Art”.Contrasts emerge in their profiles:“Law”topics are internally consistent,“History”topics diffuse across disciplines,and“Literature”is consistently classified when modal but tends to be overattributed otherwise.Research limitations/implications:The results reflect the scope of VABB-SHW and the narrow definition of“local”.Topic descriptions and disciplinary expectations may introduce uncertainty.The findings are not directly generalizable,but the approach can be replicated in other national databases and with broader definitions to test robustness.Practical implications:The approach illustrates how national bibliographic databases can be systematically analysed to identify and profile locally anchored research,offering a basis for comparative studies across regions.Originality/value:This is the first study to systematically analyse local topics in VABB-SHW,combining topic modelling and content-based classification to highlight how SSH research engages with nationally specific issues. 展开更多
关键词 topic analysis local topics SSH research classification VABB-SHW
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基于BERTopic模型的国外数字健康素养研究及启示 认领 引用
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作者 王崇祥 陈俊冶 +1 位作者 贾希 刘鸿齐 《中国卫生质量管理》 2026年第8期68-73,共6页
目的通过对国外数字健康素养的文献数据进行挖掘分析,探讨当前数字健康素养研究现状,为我国数字健康素养研究提供参考。方法基于PubMed数据库,系统检索2014—2024年期间发表的数字健康素养相关文献,借助BERTopic模型进行主题提取与识别... 目的通过对国外数字健康素养的文献数据进行挖掘分析,探讨当前数字健康素养研究现状,为我国数字健康素养研究提供参考。方法基于PubMed数据库,系统检索2014—2024年期间发表的数字健康素养相关文献,借助BERTopic模型进行主题提取与识别,分析研究主题和主题演化趋势。结果从发文量来看,国外数字健康素养领域发文量整体呈上升趋势,研究内容主要涵盖4个主题:患者护理、青少年心理健康、母婴健康、人工智能应用。其中,患者护理热度最高,其余主题热度总体变化呈现稳中有涨的趋势。结论借鉴国际先进经验的同时,我国数字健康素养研究应聚焦本土人群特征与健康需求,通过构建医患协同的数字素养提升体系,强化多主体联动的青少年心理健康干预,拓展重点人群的数字健康服务覆盖,并推进人工智能技术的普惠应用,系统性提升数字健康治理能力与全民健康福祉。 展开更多
关键词 数字健康素养 主题分析 BERTopic模型
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特朗普主义的集体叙事——基于BERTopic与情感分析的特朗普政府核心人物文本探析 认领 引用
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作者 陈旭海 吕家璇 郑志恒 《情报探索》 2026年第5期44-55,共12页
[目的/意义]揭示特朗普主义意识形态的内在结构及其叙事动员机制,分析其在全球右翼浪潮中的典型性与风险,并为理解当代右翼政治的叙事逻辑提供一种新的分析视角。[方法/过程]以六位特朗普政府核心成员在就职前撰写的代表性著作为主要分... [目的/意义]揭示特朗普主义意识形态的内在结构及其叙事动员机制,分析其在全球右翼浪潮中的典型性与风险,并为理解当代右翼政治的叙事逻辑提供一种新的分析视角。[方法/过程]以六位特朗普政府核心成员在就职前撰写的代表性著作为主要分析文本,采用BERTopic主题建模与情感分析方法,识别其关键议题、情感动员方式与敌我划分机制;结合政治叙事分析框架,对其意识形态塑造路径与话语逻辑进行系统阐释。[结果/结论]特朗普主义通过将复杂社会现实简化为道德对立结构,并借助愤怒、焦虑与希望等情绪强化政治动员,其并非单一人物风格的体现,而是一套具备高度一致性与可复制性的意识形态话语,加剧了民主规范的侵蚀与社会极化。 展开更多
关键词 特朗普主义 主题建模 情感分析
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Optimization Analysis of Campus Topic Space in Colleges and Universities——A Case Study of the Colleges and Universities in Lishui, Zhejiang Province 认领 引用
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作者 李田 高依洁 胡牮 《Agricultural Science & Technology》 CAS 2017年第12期2571-2575,共5页
University campus is the most important place for life, study, activity and experience of contemporary college students. It is helpful for students to survive and develop to create the topic space of campus. Taking th... University campus is the most important place for life, study, activity and experience of contemporary college students. It is helpful for students to survive and develop to create the topic space of campus. Taking the topic space of college campuses in Lishui City of Zhejiang Province as an example, the current situations are analyzed through questionnaire survey and field visit. The results show that uni- versity campus space needs a clear topic; the demands are generally large for the topics of exchange and communication, learning and thinking, sports and leisure in all kinds of space; the creation of these types of topic spaces should focus on the peaceful environment, beautiful scenery, privacy of the space and WlFI coverage. 展开更多
关键词 Campus topic space Optimization analysis Colleges and universities Lishui City
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基于BERTopic的医疗质量管理政策文本主题分析 认领 引用
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作者 孙少华 乔庆玲 +2 位作者 单凯 张国宗 朱明 《中国卫生政策研究》 CSCD 北大核心 2026年第4期26-33,共8页
目的:对我国医疗质量管理政策文本进行主题识别与分析。方法:收集2009—2025年国家层面发布的医疗质量管理相关政策文本,运用BERTopic主题建模方法进行主题识别与系统分析。结果:共纳入政策文本626份,聚类形成19个核心主题,归纳为两大... 目的:对我国医疗质量管理政策文本进行主题识别与分析。方法:收集2009—2025年国家层面发布的医疗质量管理相关政策文本,运用BERTopic主题建模方法进行主题识别与系统分析。结果:共纳入政策文本626份,聚类形成19个核心主题,归纳为两大类五个维度:第一类聚焦临床实践与资源管理,涵盖手术-住院-资源闭环管理以及技术支撑与患者安全的协同推进;第二类关注体系优化与政策协同,体现为人力资本投入与人文关怀并重、预防-治疗-康复一体化服务体系建设以及传统医学现代化与创新技术监管的并行发展。结论:我国医疗质量管理政策顺应卫生健康事业改革发展的演进脉络,主题呈现临床纵深治理与体系横向整合特征,已形成制度-技术-资源-人文立体化体系,正从经验管理向循证管理、从管控向共治、从以治疗为中心向以健康为中心转型,但仍面临法治化基础有待强化以及协调性、可操作性、人文性不足等挑战,未来可通过多模型协同与时空演变分析进一步深化研究。 展开更多
关键词 医疗质量管理政策 BERTopic 主题挖掘 文本分析
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Investigating public perceptions regarding the Long COVID on Twitter using sentiment analysis and topic modeling 认领 引用
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作者 Yu-Bo Fu 《Medical Data Mining》 2022年第4期56-61,共6页
Background:An estimated 10 to 30 percent of people who become infected with Severe acute respiratory syndrome coronavirus 2 will experience persistent symptoms after recovering from Coronavirus Disease 2019(COVID-19),... Background:An estimated 10 to 30 percent of people who become infected with Severe acute respiratory syndrome coronavirus 2 will experience persistent symptoms after recovering from Coronavirus Disease 2019(COVID-19),which is known as Long COVID.Social media platforms like Facebook and Twitter are the primary sources to gather and examine people’s opinion and sentiments towards various topics.Methods:In this paper,we aimed to examine sentiments,discover key themes and associated topics in Long COVID-related messages posted by Twitter users in the US between March 2022 and April 2022 using sentiment analysis and topic modeling.Results:A total of 117,789 tweets were examined,of which three dominant themes were identified,ranging from symptoms to social and economic impacts,and preventive measures.We also found that more negative sentiments were expressed in the tweets by users toward long-term COVID-19.Conclusions:Our research throws light on dominant themes,topics and sentiments surrounding the ongoing public health crisis.From the insights gained,we discuss the major implications of this study for health practitioners and policymakers. 展开更多
关键词 Long COVID Twitter social media sentiment analysis topic modeling
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基于BERTopic的高等教育生成式人工智能研究主题识别与内容分析 认领 引用
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作者 韩丽 许洁 罗晓兰 《大学图书情报学刊》 2026年第2期72-79,共8页
生成式人工智能正深刻变革教育,相关研究文献不断涌现。文章通过收集知网、Scopus和Web of Science中与研究主题相关的中英文文献,利用BERTopic主题建模技术对文献进行主题聚类,挖掘国内外高等教育中生成式人工智能的研究主题,分析研究... 生成式人工智能正深刻变革教育,相关研究文献不断涌现。文章通过收集知网、Scopus和Web of Science中与研究主题相关的中英文文献,利用BERTopic主题建模技术对文献进行主题聚类,挖掘国内外高等教育中生成式人工智能的研究主题,分析研究现状,为教育领域的教学实践和学术研究提供参考。研究结果表明:在个性化学习与人机协同方面,生成式人工智能通过制定个性化学习路径显著提升教学效果;师生对生成式人工智能的接受程度受技术认知和使用体验等因素制约,并直接影响应用成效;教育创新需平衡技术赋能与过度依赖问题;教学设计与课程实践的革新更多体现在教学模式和资源生成方式上,但必须同步构建学术伦理防护与治理机制;人工智能时代亟须人才培养结构的优化升级,要求教育者重新定义核心能力目标。 展开更多
关键词 BERTopic 高等教育 生成式人工智能 研究主题识别 内容分析
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基于BERTopic模型的我国农业生态产品价值研究主题识别与分析 认领 引用
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作者 王巧巧 龚翔 +1 位作者 张利辉 孔德瀚 《河北环境工程学院学报》 CAS 2026年第4期52-59,共8页
为厘清我国农业生态产品价值研究领域的知识结构与演变脉络,以CNKI收录的921篇文献为样本,运用BERTopic主题模型识别研究主题,并结合层次聚类方法对主题进行聚合分析。结果共识别出13个稳定主题,进一步聚合为四大研究方向:农业生态补偿... 为厘清我国农业生态产品价值研究领域的知识结构与演变脉络,以CNKI收录的921篇文献为样本,运用BERTopic主题模型识别研究主题,并结合层次聚类方法对主题进行聚合分析。结果共识别出13个稳定主题,进一步聚合为四大研究方向:农业生态补偿与农户行为机制、环境资源协同与生态扶贫减贫、生态产品价值实现与市场化机制、生态旅游与社区可持续发展。四大研究方向构成该领域的核心知识框架,研究主题呈现从补偿机制到市场化路径的演化特征。时间演化分析结果显示:2014—2025年研究热点经历3个阶段转变,即从传统补偿主导转向多元协同,再转向市场化价值实现;研究重心从成本评估转向多目标协同,进而转向市场化机制设计。 展开更多
关键词 农业生态产品价值 主题识别 BERTopic 生态补偿 演化分析
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