Mapping Data-Driven Research Impact Science: The Role of Machine Learning and Artificial Intelligence
Abstract
:1. Introduction
- What is the current status of research impact evaluation using machine learning and artificial intelligence?
- What are the prominent methodologies and emerging research themes in applying machine learning and artificial intelligence to research impact assessment?
- What are the key directions for future research in integrating advanced computational techniques into multidimensional research impact evaluation?
2. Review of Literature
2.1. Advancing Research Impact Evaluation Through Data Science and Computational Methods
2.2. Bibliometric Analysis Overview
2.3. Topic Modelling for Thematic Analysis
3. Methodology
3.1. Data Collection and Preparation
3.1.1. Stage 1: Search Strategy
3.1.2. Stage 2: Results Screening and Refinement
3.2. Bibliometric Analysis
- Co-authorship networks were used to map collaborative patterns among researchers, institutions, and countries, revealing key influencers and research clusters.
- Co-occurrence networks were employed to analyse frequently appearing keywords, enabling the identification of emerging themes and dominant research areas.
- Citation networks measured direct academic influence, helping to trace the impact of seminal papers.
- Co-citation networks identified intellectual connections by linking papers frequently cited, reflecting conceptual relationships within the field.
- Bibliographic coupling was used to group papers sharing standard references, highlighting emerging research directions and potential knowledge gaps.
- Researchers’ Analysis: Evaluated authors’ productivity and impact, mapping various networks among authors.
- Institution Analysis: Assessed institutional productivity and explored collaborative networks to gauge the influence among institutions.
- Country Analysis: Analysed productivity and network dynamics at the country level, providing insights into global research collaborations.
- Publication Source Analysis: Investigated the roles of various journals and venues through productivity metrics and network analysis.
- Document Analysis: Conducted a detailed analysis of documents to map citation networks and identify critical publications.
- Keyword Analysis: Utilized co-occurrence analysis of authors’ keywords and KeyWords Plus to identify prevalent and emerging themes.
3.3. Topic Modelling
4. Results
4.1. Analysis of Published Documents
4.1.1. Document Citation Analysis
4.1.2. Document Co-Citation Analysis
4.1.3. Document Bibliographic Coupling Analysis
4.1.4. Document Citation Burst Analysis
4.2. Analysis of Publication Sources
4.2.1. Publication Citation Analysis
4.2.2. Publication Co-Citation Analysis
4.2.3. Publication Bibliographic Coupling Analysis
4.3. Analysis of Researchers
4.3.1. Researchers’ Co-Authorship Analysis
4.3.2. Researchers’ Citation Analysis
4.3.3. Researchers’ Co-Citation Analysis
4.3.4. Researchers’ Bibliographic Coupling Analysis
4.4. Analysis of Institutions
4.4.1. Institutions’ Co-Authorship Analysis
4.4.2. Institutions’ Citation Analysis
4.4.3. Institutions’ Bibliographic Coupling Analysis
4.5. Analysis of Countries
4.5.1. Countries’ Co-Authorship Analysis
4.5.2. Countries’ Citation Analysis
4.5.3. Countries’ Bibliographic Coupling Analysis
4.6. Analysis of Research
4.6.1. Authors’ Keyword Analysis
4.6.2. Associated Keyword Analysis
4.6.3. Research Topic Analysis
5. Discussion
5.1. Overview of the Key Findings
5.2. Prominent Methodologies and Emerging Research Themes in Machine Learning and Artificial Intelligence for Research Impact Assessment
5.3. Future Directions for Integrating Advanced Computational Techniques into Multidimensional Research Impact Evaluation
5.4. Implications and Limitations of the Study
6. Conclusions
Author Contributions
Funding
Data Availability Statement
Conflicts of Interest
Appendix A. Topic Modelling Outcomes
Scholarly Interpretation | Topic Modelling Result | |||||||
---|---|---|---|---|---|---|---|---|
Group | Interpreted Topic Label | Topic | Count | LLama2 Label | Name | Representation | KeyBERT | MMR |
Bibliometric and Scientometric Analysis in AI and ML Research | Topic Modelling and Research Trend Analysis in Scholarly Literature | 0 | 215 | Research Impact Analysis and Prediction | 0_topic_modeling_influence_analysis | [‘topic’, ‘modeling’, ‘influence’, ‘analysis’, ‘text’, ‘trend’, ‘network’, ‘processing’, ‘social’, ‘mining’, ‘natural’, ‘science’, ‘language’, ‘latent’, ‘evolution’, ‘dirichlet’, ‘allocation’, ‘technology’, ‘scientometrics’, ‘patent’, ‘lda’, ‘bibliometrics’, ‘model’, ‘research’, ‘using’, ‘information’, ‘citation’, ‘emerging’, ‘study’, ‘bibliometric’, ‘knowledge’, ‘scientific’, ‘twitter’, ‘similarity’, ‘dynamic’, ‘clustering’, ‘medium’, ‘detection’, ‘prediction’, ‘collaboration’, ‘approach’, ‘machine’, ‘literature’, ‘data’, ‘publication’, ‘library’, ‘forecasting’, ‘extraction’, ‘identifying’, ‘word’, ‘cocitation’, ‘innovation’, ‘community’, ‘structure’, ‘index’, ‘semantic’, ‘news’, ‘speech’, ‘review’, ‘learning’, ‘interdisciplinarity’, ‘brain’, ‘nlp’, ‘hierarchical’, ‘indicator’, ‘time’, ‘sentiment’, ‘based’, ‘technological’, ‘cluster’, ‘bibliographic’, ‘translation’, ‘path’, ‘framework’, ‘document’, ‘scientometric’, ‘diffusion’, ‘analyzing’, ‘market’, ‘author’, ‘profiling’, ‘informationscience’, ‘convergence’, ‘classification’, ‘graph’, ‘method’, ‘centrality’, ‘series’, ‘event’, ‘detecting’, ‘topical’, ‘trending’, ‘mass’, ‘coword’, ‘core’, ‘management’, ‘hybrid’, ‘impact’, ‘chinese’, ‘feature’] | [‘scientometrics’, ‘bibliometrics’, ‘scientometric’, ‘bibliometric’, ‘informationscience’, ‘latent’, ‘topical’, ‘topic’, ‘centrality’, ‘classification’] | [‘scientometrics’, ‘lda’, ‘bibliometrics’, ‘bibliometric’, ‘interdisciplinarity’, ‘nlp’, ‘scientometric’, ‘informationscience’, ‘centrality’, ‘trending’] |
Research Evaluation Using Altmetrics and Citation Analysis in Scholarly Communication | 1 | 65 | Impact Analysis and Prediction in Scholarly Research | 1_altmetrics_twitter_sentiment_social | [‘altmetrics’, ‘twitter’, ‘sentiment’, ‘social’, ‘regression’, ‘medium’, ‘linear’, ‘tweet’, ‘emotional’, ‘analysis’, ‘data’, ‘big’, ‘opinion’, ‘multiple’, ‘journal’, ‘evaluation’, ‘impact’, ‘altmetric’, ‘utility’, ‘scholarly’, ‘research’, ‘communication’, ‘article’, ‘influence’, ‘review’, ‘academic’, ‘quality’, ‘based’, ‘government’, ‘satisfaction’, ‘public’, ‘medicine’, ‘perception’, ‘effect’, ‘score’, ‘citation’, ‘machine’, ‘attachment’, ‘microblog’, ‘network’, ‘user’, ‘set’, ‘scholar’, ‘air’, ‘metric’, ‘facebook’, ‘fuzzy’, ‘online’, ‘news’, ‘life’, ‘researcher’, ‘approach’, ‘geographically’, ‘mentioning’, ‘science’, ‘learning’, ‘subjective’, ‘scale’, ‘agreement’, ‘pca’, ‘factor’, ‘ranking’, ‘model’, ‘usage’, ‘excellence’, ‘humanity’, ‘study’, ‘bias’, ‘significance’, ‘google’, ‘predicting’, ‘statistic’, ‘weighted’, ‘time’, ‘book’, ‘influential’, ‘attention’, ‘feature’, ‘mining’, ‘technology’, ‘legal’, ‘correlation’, ‘typology’, ‘dsrs’, ‘scenic’, ‘lightweight’, ‘housing’, ‘specialized’, ‘societal’, ‘retweet’, ‘researchgate’, ‘mention’, ‘neurosexism’, ‘goodreads’, ‘youtube’, ‘timeweighted’, ‘neuraminidase’, ‘psolstm’, ‘revised’, ‘renewal’] | [‘altmetrics’, ‘altmetric’, ‘weighted’, ‘ranking’, ‘scholarly’, ‘influential’, ‘researchgate’, ‘impact’, ‘researcher’, ‘twitter’] | [‘altmetrics’, ‘twitter’, ‘altmetric’, ‘citation’, ‘factor’, ‘ranking’, ‘weighted’, ‘influential’, ‘researchgate’, ‘timeweighted’] | |
Bibliometric Analysis of Artificial Intelligence Research | 2 | 54 | Artificial Intelligence for Research Impact Analysis | 2_language_chatgpt_artificial_chatbot | [‘language’, ‘chatgpt’, ‘artificial’, ‘chatbot’, ‘intelligence’, ‘writing’, ‘generative’, ‘ai’, ‘automated’, ‘education’, ‘english’, ‘bibliometric’, ‘learning’, ‘chatbots’, ‘teacher’, ‘conversational’, ‘assessment’, ‘tutoring’, ‘analysis’, ‘natural’, ‘intelligent’, ‘chemistry’, ‘processing’, ‘essay’, ‘foreignlanguage’, ‘efl’, ‘agent’, ‘bibliometrics’, ‘organic’, ‘large’, ‘research’, ‘emergency’, ‘personalized’, ‘validity’, ‘use’, ‘future’, ‘feedback’, ‘review’, ‘trend’, ‘professional’, ‘literature’, ‘second’, ‘evaluation’, ‘comprehensive’, ‘learner’, ‘comprehension’, ‘technology’, ‘foreign’, ‘exploring’, ‘year’, ‘metaanalysis’, ‘cocitation’, ‘biology’, ‘model’, ‘systematic’, ‘hallucination’, ‘intelligenceassisted’, ‘resuscitation’, ‘secondyear’, ‘technologybased’, ‘metaanalytic’, ‘triage’, ‘council’, ‘learningsystem’, ‘obgyn’, ‘captcha’, ‘ajg’, ‘l2’, ‘aiassisted’, ‘whatsapp’, ‘gpt’, ‘breaking’, ‘biofeedback’, ‘altmetrics’, ‘application’, ‘artificialintelligence’, ‘testing’, ‘congress’, ‘written’, ‘breast’, ‘jcr’, ‘practice’, ‘system’, ‘mechanism’, ‘crosssectional’, ‘chatgpt35’, ‘bot’, ‘survey’, ‘student’, ‘science’, ‘dimensionsai’, ‘viewer’, ‘realtime’, ‘interpretation’, ‘vos’, ‘snip’, ‘reconstruction’, ‘reaction’, ‘teaching’, ‘knowledge’] | [‘bibliometric’, ‘bibliometrics’, ‘altmetrics’, ‘artificialintelligence’, ‘ai’, ‘chatbots’, ‘aiassisted’, ‘chatbot’, ‘survey’, ‘systematic’] | [‘chatgpt’, ‘ai’, ‘chatbots’, ‘assessment’, ‘learningsystem’, ‘captcha’, ‘aiassisted’, ‘altmetrics’, ‘artificialintelligence’, ‘bot’] | |
Bibliometric and Scientometric Analysis of Artificial Intelligence in Education | 9 | 43 | Artificial Intelligence in Education and Research | 9_education_intelligence_artificial_bibliometric | [‘education’, ‘intelligence’, ‘artificial’, ‘bibliometric’, ‘chatgpt’, ‘higher’, ‘educational’, ‘technology’, ‘generative’, ‘ai’, ‘analysis’, ‘nursing’, ‘student’, ‘academic’, ‘research’, ‘review’, ‘literature’, ‘entrepreneurship’, ‘learning’, ‘specialization’, ‘20132023’, ‘personalised’, ‘special’, ‘speech’, ‘plagiarism’, ‘curriculum’, ‘integrity’, ‘analytics’, ‘trend’, ‘interdisciplinary’, ‘future’, ‘entrepreneurial’, ‘environment’, ‘year’, ‘science’, ‘language’, ‘direction’, ‘knowledge’, ‘systematic’, ‘bard’, ‘3dgpt’, ‘iraq’, ‘internationalisation’, ‘competencybased’, ‘dishonesty’, ‘challenge’, ‘bibliometrics’, ‘citespace’, ‘performance’, ‘school’, ‘development’, ‘technologyenhanced’, ‘field’, ‘mapping’, ‘unveiling’, ‘mechanical’, ‘profession’, ‘secondary’, ‘map’, ‘engineering’, ‘africa’, ‘style’, ‘decade’, ‘management’, ‘need’, ‘content’, ‘soft’, ‘study’, ‘institution’, ‘implication’, ‘topic’, ‘application’, ‘website’, ‘tutoring’, ‘pedagogy’, ‘emerging’, ‘natural’, ‘strategic’, ‘capability’, ‘agenda’, ‘literacy’, ‘european’, ‘business’, ‘adaptive’, ‘orientation’, ‘web’, ‘40’, ‘manufacturing’, ‘country’, ‘artificialintelligence’, ‘teaching’, ‘insight’, ‘evolution’, ‘landscape’, ‘online’, ‘perception’, ‘scientific’, ‘covid19’, ‘role’, ‘vosviewer’] | [‘bibliometric’, ‘bibliometrics’, ‘artificialintelligence’, ‘systematic’, ‘education’, ‘ai’, ‘institution’, ‘academic’, ‘knowledge’, ‘educational’] | [‘education’, ‘bibliometric’, ‘chatgpt’, ‘plagiarism’, ‘analytics’, ‘bard’, ‘citespace’, ‘emerging’, ‘artificialintelligence’, ‘online’] | |
Research Impact Through Bibliometric, Scientometric, and Multivariate Analysis | 10 | 39 | Machine Learning for Research Impact Analysis | 10_principal_component_heuristic_bibliometricsbased | [‘principal’, ‘component’, ‘heuristic’, ‘bibliometricsbased’, ‘performance’, ‘evaluation’, ‘research’, ‘regression’, ‘indicator’, ‘analysis’, ‘frugal’, ‘university’, ‘logistic’, ‘hindex’, ‘agricultural’, ‘scientific’, ‘psychological’, ‘index’, ‘website’, ‘science’, ‘decision’, ‘sector’, ‘institute’, ‘researcher’, ‘personal’, ‘rd’, ‘model’, ‘impact’, ‘public’, ‘method’, ‘appraisal’, ‘bibliometrics’, ‘measure’, ‘higher’, ‘output’, ‘multivariate’, ‘development’, ‘innovation’, ‘cost’, ‘using’, ‘institution’, ‘investment’, ‘level’, ‘mmre’, ‘pred’, ‘herzegovina’, ‘revolutionary’, ‘bosnia’, ‘nobel’, ‘estonia’, ‘ordinal’, ‘prizewinning’, ‘coping’, ‘mainland’, ‘journal’, ‘efficiency’, ‘chinese’, ‘production’, ‘activity’, ‘data’, ‘multinomial’, ‘thesis’, ‘restart’, ‘subsidy’, ‘display’, ‘staff’, ‘factor’, ‘ranking’, ‘decisionmaking’, ‘growth’, ‘tree’, ‘judgment’, ‘wellbeing’, ‘department’, ‘envelopment’, ‘lens’, ‘citation’, ‘based’, ‘delphi’, ‘visibility’, ‘confidence’, ‘agriculture’, ‘definition’, ‘bibliometric’, ‘linear’, ‘big’, ‘stress’, ‘coauthor’, ‘individual’, ‘cell’, ‘uncertainty’, ‘policy’, ‘productivity’, ‘choice’, ‘doctoral’, ‘disciplinary’, ‘economic’, ‘stem’, ‘case’, ‘difference’] | [‘bibliometric’, ‘bibliometrics’, ‘bibliometrics-based’, ‘ranking’, ‘citation’, ‘evaluation’, ‘institution’, ‘appraisal’, ‘envelopment’, ‘multivariate’] | [‘heuristic’, ‘bibliometrics-based’, ‘indicator’, ‘institute’, ‘bibliometrics’, ‘multivariate’, ‘ranking’, ‘envelopment’, ‘citation’, ‘bibliometric’] | |
Bibliometric and Scientometric Analysis of Machine Learning and Educational Technology | 18 | 26 | Artificial Intelligence and Scientific Impact Analysis | 18_intelligence_artificial_bibliometric_analysis | [‘intelligence’, ‘artificial’, ‘bibliometric’, ‘analysis’, ‘adoption’, ‘science’, ‘technology’, ‘maritime’, ‘crime’, ‘study’, ‘pattern’, ‘ai’, ‘trend’, ‘management’, ‘humancomputer’, ‘bibliometrics’, ‘system’, ‘vehicle’, ‘thematic’, ‘knowledge’, ‘branding’, ‘unscented’, ‘luxury’, ‘agentbased’, ‘kalman’, ‘autonomous’, ‘ukf’, ‘suspicious’, ‘production’, ‘application’, ‘applied’, ‘artificialintelligence’, ‘filter’, ‘mapping’, ‘scientometric’, ‘transformerbased’, ‘research’, ‘basic’, ‘union’, ‘property’, ‘decade’, ‘scenario’, ‘robotics’, ‘evolution’, ‘interaction’, ‘air’, ‘tracking’, ‘space’, ‘scientific’, ‘entrepreneurial’, ‘intelligent’, ‘keyword’, ‘strategy’, ‘recent’, ‘european’, ‘transformation’, ‘complex’, ‘coword’, ‘model’, ‘indicator’, ‘40’, ‘activity’, ‘prediction’, ‘intellectual’, ‘quality’, ‘landscape’, ‘domain’, ‘impact’, ‘generative’, ‘output’, ‘automatic’, ‘vosviewer’, ‘innovation’, ‘19822019’, ‘iapplied’, ‘aerial’, ‘socialmedia’, ‘kg4ai’, ‘30th’, ‘19602021’, ‘strategicmanagement’, ‘iso’, ‘iscimati’, ‘20072016’, ‘auv’, ‘tendency’, ‘aerospace’, ‘unmanned’, ‘anniversary’, ‘hcii’, ‘aiinfused’, ‘navigation’, ‘adapts’, ‘scopusbased’, ‘90012015’, ‘competitiveness’, ‘involving’, ‘right’, ‘burberry’, ‘dispersion’] | [‘scientometric’, ‘bibliometric’, ‘bibliometrics’, ‘scopusbased’, ‘artificialintelligence’, ‘ai’, ‘humancomputer’, ‘intelligence’, ‘aiinfused’, ‘knowledge’] | [‘trend’, ‘bibliometrics’, ‘kalman’, ‘artificialintelligence’, ‘scientometric’, ‘complex’, ‘19822019’, ‘auv’, ‘unmanned’, ‘aiinfused’] | |
Bibliometric and ML/AI-Enhanced Analysis of Sustainable Development and Technological Innovations | 16 | 27 | Artificial Intelligence for Business Management and Innovation | 16_business_management_cocitation_digital | [‘business’, ‘management’, ‘cocitation’, ‘digital’, ‘modeling’, ‘creativity’, ‘topic’, ‘intellectual’, ‘structure’, ‘transformation’, ‘innovation’, ‘analysis’, ‘knowledge’, ‘industry’, ‘marketing’, ‘acceptance’, ‘system’, ‘entrepreneurship’, ‘field’, ‘bibliometric’, ‘model’, ‘manufacturing’, ‘40’, ‘logistics’, ‘informationtechnology’, ‘evolution’, ‘dynamic’, ‘big’, ‘hot’, ‘cooccurrence’, ‘trend’, ‘technology’, ‘citation’, ‘economics’, ‘scientometric’, ‘waste’, ‘science’, ‘strategic’, ‘iiot’, ‘utaut’, ‘territorial’, ‘fieldconfiguring’, ‘selfservice’, ‘chain’, ‘supply’, ‘bibliometrics’, ‘healthcare’, ‘analytics’, ‘data’, ‘pharmacy’, ‘landscape’, ‘modelling’, ‘electric’, ‘intelligence’, ‘approach’, ‘rural’, ‘customer’, ‘trust’, ‘digitalization’, ‘forecasting’, ‘informationsystems’, ‘software’, ‘service’, ‘artificial’, ‘social’, ‘selfcitation’, ‘advanced’, ‘corporate’, ‘datadriven’, ‘intention’, ‘governance’, ‘mobility’, ‘culture’, ‘impact’, ‘keyword’, ‘strategy’, ‘optimization’, ‘event’, ‘future’, ‘adoption’, ‘industrial’, ‘coword’, ‘understanding’, ‘medium’, ‘mapping’, ‘component’, ‘engineering’, ‘environmental’, ‘construction’, ‘neuralnetworks’, ‘decisionmaking’, ‘finance’, ‘development’, ‘design’, ‘research’, ‘kads’, ‘introduction’, ‘germany’, ‘hospitality’, ‘gephi’] | [‘bibliometric’, ‘bibliometrics’, ‘scientometric’, ‘digitalization’, ‘citation’, ‘informationtechnology’, ‘knowledge’, ‘cocitation’, ‘analytics’, ‘dynamic’] | [‘cocitation’, ‘entrepreneurship’, ‘40’, ‘dynamic’, ‘trend’, ‘scientometric’, ‘iiot’, ‘bibliometrics’, ‘analytics’, ‘digitalization’] | |
Bibliometric and Scientometric Analysis of Machine Learning and Educational Technology | 26 | 16 | Machine Learning for Education Research Impact Analysis | 26_analytics_modeling_topic_education | [‘analytics’, ‘modeling’, ‘topic’, ‘education’, ‘educational’, ‘preservation’, ‘analysis’, ‘contributor’, ‘bibliometric’, ‘decade’, ‘system’, ‘machine’, ‘technology’, ‘syllabus’, ‘learning’, ‘structural’, ‘rpackage’, ‘mainstream’, ‘bibliometrics’, ‘bibliometrix’, ‘multimodal’, ‘network’, ‘conference’, ‘digital’, ‘information’, ‘insight’, ‘social’, ‘blockchain’, ‘predictive’, ‘trend’, ‘based’, ‘technologyi’, ‘ibritish’, ‘tinyml’, ‘tiny’, ‘fontana’, ‘salient’, ‘cs1an’, ‘revalidation’, ‘presented’, ‘deciphering’, ‘disadvantage’, ‘edm’, ‘edtech’, ‘learningexperiences’, ‘universitystudents’, ‘academicachievement’, ‘tinymledu’, ‘smart’, ‘year’, ‘predicting’, ‘mi’, ‘analyzer’, ‘20082019’, ‘embedded’, ‘management’, ‘data’, ‘package’, ‘twentyfive’, ‘aspect’, ‘higher’, ‘research’, ‘point’, ‘initiative’, ‘ict’, ‘repository’, ‘open’, ‘collaboration’, ‘networking’, ‘cooccurrence’, ‘learningbased’, ‘negative’, ‘highereducation’, ‘openaccess’, ‘joint’, ‘privacy’, ‘theme’, ‘impact’, ‘keyword’, ‘material’, ‘mining’, ‘problem’, ‘success’, ‘coword’, ‘knowledge’, ‘task’, ‘analyzing’, ‘journal’, ‘institutional’, ‘school’, ‘applied’, ‘study’, ‘acceptance’, ‘intellectual’, ‘satisfaction’, ‘using’, ‘covid19’, ‘work’, ‘metadata’, ‘teacher’] | [‘bibliometrics’, ‘bibliometric’, ‘bibliometrix’, ‘edtech’, ‘presented’, ‘institutional’, ‘learningexperiences’, ‘education’, ‘learningbased’, ‘knowledge’] | [‘analytics’, ‘education’, ‘contributor’, ‘bibliometrics’, ‘bibliometrix’, ‘edtech’, ‘learningexperiences’, ‘tinymledu’, ‘learningbased’, ‘institutional’] | |
Bibliometric and Scientometric Analysis of Artificial Intelligence Research Trends and Applications | 25 | 17 | Machine Learning for Bibliometric Analysis | 25_bibliometric_face_visualization_failure | [‘bibliometric’, ‘face’, ‘visualization’, ‘failure’, ‘fuzzy’, ‘trend’, ‘machine’, ‘distribution’, ‘analysis’, ‘mapping’, ‘intelligence’, ‘visual’, ‘damage’, ‘artificial’, ‘recognition’, ‘neuralnetwork’, ‘birnbaumsaunders’, ‘fatigue’, ‘streamflow’, ‘textile’, ‘epilepsy’, ‘cumulative’, ‘softwaredefined’, ‘deepfakes’, ‘cartography’, ‘anesthesia’, ‘citespace’, ‘prediction’, ‘land’, ‘log’, ‘deep’, ‘learning’, ‘networking’, ‘vector’, ‘defect’, ‘life’, ‘pattern’, ‘material’, ‘detection’, ‘thematic’, ‘knowledge’, ‘support’, ‘classification’, ‘manufacturing’, ‘neural’, ‘statistical’, ‘network’, ‘algorithm’, ‘neuralnetworks’, ‘representation’, ‘evolution’, ‘landscape’, ‘vision’, ‘map’, ‘vosviewer’, ‘bibliometrics’, ‘model’, ‘research’, ‘coordinate’, ‘period’, ‘organiccarbon’, ‘iexpert’, ‘2004’, ‘inspection’, ‘waterlevel’, ‘2dimensional’, ‘vosviewerbased’, ‘19902019’, ‘landslide’, ‘soil’, ‘bibliometrical’, ‘subfields’, ‘microassembly’, ‘dematel’, ‘roughness’, ‘riskevaluation’, ‘proposition’, ‘fnn’, ‘radical’, ‘preserving’, ‘corrosion’, ‘suitability’, ‘mle’, ‘diagnostics’, ‘avoid’, ‘truncated’, ‘fabric’, ‘fake’, ‘aisdn’, ‘susceptibility’, ‘applicationsi’, ‘year’, ‘science’, ‘technique’, ‘rstudio’, ‘logisticregression’, ‘condition’, ‘prominent’, ‘seizure’, ‘cosine’] | [‘bibliometric’, ‘bibliometrics’, ‘bibliometrical’, ‘classification’, ‘citespace’, ‘knowledge’, ‘neuralnetwork’, ‘neuralnetworks’, ‘research’, ‘statistical’] | [‘machine’, ‘textile’, ‘deepfakes’, ‘citespace’, ‘classification’, ‘neuralnetworks’, ‘bibliometrics’, ‘model’, ‘iexpert’, ‘aisdn’] | |
Bibliometric Analysis and Research Evaluation of Metaheuristic Algorithms | 3 | 51 | Optimization and Machine Learning in Research Impact Analysis | 3_optimization_algorithm_swarm_particle | [‘optimization’, ‘algorithm’, ‘swarm’, ‘particle’, ‘genetic’, ‘evolutionary’, ‘quantum’, ‘error’, ‘evaluation’, ‘pso’, ‘metaheuristics’, ‘colony’, ‘research’, ‘improved’, ‘ant’, ‘oxidation’, ‘design’, ‘problem’, ‘reliability’, ‘independent’, ‘combinatorial’, ‘function’, ‘bibliometric’, ‘cognitive’, ‘based’, ‘law’, ‘station’, ‘flatness’, ‘psosvm’, ‘subway’, ‘dance’, ‘inspired’, ‘seismic’, ‘camouflage’, ‘quantuminspired’, ‘computing’, ‘network’, ‘metaheuristic’, ‘method’, ‘effect’, ‘radio’, ‘annealing’, ‘art’, ‘performance’, ‘simulated’, ‘order’, ‘search’, ‘analysis’, ‘scheduling’, ‘signal’, ‘journal’, ‘flexible’, ‘component’, ‘multiobjective’, ‘model’, ‘fusion’, ‘catalyst’, ‘dysfunction’, ‘camoevo’, ‘pursuit’, ‘vanet’, ‘scanning’, ‘mdo’, ‘rod’, ‘deteriorating’, ‘roundness’, ‘fishery’, ‘bioeconomic’, ‘multipopulation’, ‘pipe’, ‘shop’, ‘array’, ‘wideangle’, ‘rectal’, ‘vehicular’, ‘connecting’, ‘waterlogging’, ‘compression’, ‘antenna’, ‘kinetics’, ‘holographic’, ‘jobshop’, ‘chaos’, ‘phased’, ‘neural’, ‘application’, ‘selection’, ‘strategy’, ‘resilience’, ‘objective’, ‘thyroid’, ‘routing’, ‘riskassessment’, ‘managerial’, ‘sampling’, ‘nature’, ‘disaster’, ‘projection’, ‘disruption’, ‘completeness’] | [‘metaheuristics’, ‘metaheuristic’, ‘pso’, ‘algorithm’, ‘psosvm’, ‘bibliometric’, ‘optimization’, ‘method’, ‘search’, ‘multiobjective’] | [‘evolutionary’, ‘pso’, ‘metaheuristics’, ‘ant’, ‘quantuminspired’, ‘computing’, ‘metaheuristic’, ‘simulated’, ‘search’, ‘vanet’] | |
Causal Inference in Research Evaluation and Bibliometric Impact Analysis | 4 | 51 | Causal Inference and Machine Learning for Research Impact Analysis | 4_causal_inference_bayesian_risk | [‘causal’, ‘inference’, ‘bayesian’, ‘risk’, ‘effect’, ‘propensity’, ‘research’, ‘outcome’, ‘network’, ‘qualitative’, ‘estimation’, ‘policy’, ‘health’, ‘assessment’, ‘bias’, ‘method’, ‘observational’, ‘score’, ‘trial’, ‘comparative’, ‘randomization’, ‘acyclic’, ‘psychotherapy’, ‘directed’, ‘mendelian’, ‘evaluation’, ‘equipment’, ‘maintenance’, ‘epidemiology’, ‘open’, ‘journal’, ‘clinical’, ‘citation’, ‘access’, ‘based’, ‘green’, ‘medication’, ‘retracted’, ‘retraction’, ‘covariate’, ‘balance’, ‘counselling’, ‘science’, ‘effectiveness’, ‘mediation’, ‘enrollment’, ‘service’, ‘regression’, ‘impact’, ‘analysis’, ‘statistical’, ‘study’, ‘matching’, ‘injury’, ‘disease’, ‘care’, ‘probabilistic’, ‘situation’, ‘design’, ‘forecasting’, ‘fault’, ‘association’, ‘collaboration’, ‘environment’, ‘potential’, ‘interaction’, ‘randomized’, ‘significance’, ‘process’, ‘time’, ‘model’, ‘communication’, ‘simulation’, ‘feedback’, ‘hazardous’, ‘highrisk’, ‘caseonly’, ‘train’, ‘cardiovascular’, ‘endogeneity’, ‘counterfactuals’, ‘cornerstone’, ‘fall’, ‘contractor’, ‘routine’, ‘causation’, ‘moderation’, ‘gut’, ‘battlefield’, ‘ucav’, ‘microbiota’, ‘subclassification’, ‘pedestrian’, ‘graph’, ‘question’, ‘dynamic’, ‘testing’, ‘empirical’, ‘information’, ‘adjustment’] | [‘impact’, ‘empirical’, ‘citation’, ‘causal’, ‘endogeneity’, ‘covariate’, ‘effectiveness’, ‘research’, ‘study’, ‘effect’] | [‘causal’, ‘bayesian’, ‘propensity’, ‘method’, ‘acyclic’, ‘mendelian’, ‘covariate’, ‘effectiveness’, ‘endogeneity’, ‘counterfactuals’] | |
Bibliometric and Machine Learning Approaches to Analysing Research Trends and Impact in Artificial Intelligence | 20 | 20 | Machine Learning for Bibliometric Analysis | 20_neural_network_categorization_inventory | [‘neural’, ‘network’, ‘categorization’, ‘inventory’, ‘biomedical’, ‘artificial’, ‘bibliometric’, ‘technique’, ‘machine’, ‘bullwhip’, ‘chemometrics’, ‘metamethodology’, ‘data’, ‘gas’, ‘nanoparticles’, ‘associated’, ‘control’, ‘mining’, ‘oil’, ‘bibliometrics’, ‘india’, ‘keywords’, ‘logic’, ‘method’, ‘document’, ‘diagram’, ‘cell’, ‘learning’, ‘using’, ‘number’, ‘excellence’, ‘synthesis’, ‘system’, ‘law’, ‘financial’, ‘classification’, ‘supply’, ‘management’, ‘analysis’, ‘overview’, ‘fuzzy’, ‘article’, ‘scientometrics’, ‘application’, ‘collagen’, ‘neurofuzzy’, ‘chemometric’, ‘paleontology’, ‘networksbased’, ‘19912014’, ‘toxicity’, ‘19801991’, ‘reemergence’, ‘modelpredictive’, ‘bone’, ‘requires’, ‘businessrelated’, ‘nanomaterial’, ‘spotlight’, ‘gat’, ‘mark’, ‘erythrocytemembrane’, ‘encapsulation’, ‘europeanunion’, ‘membranecoated’, ‘coordination’, ‘colombia’, ‘taphonomy’, ‘historiography’, ‘hopfield’, ‘standardised’, ‘feedforward’, ‘explore’, ‘lab’, ‘graphicacy’, ‘kohonen’, ‘industry’, ‘scholarly’, ‘research’, ‘colombian’, ‘membrane’, ‘decisionsupportsystem’, ‘machinelearningbased’, ‘mini’, ‘biodiversity’, ‘biological’, ‘examine’, ‘lotka’, ‘retrieval’, ‘decision’, ‘intelligent’, ‘citation’, ‘information’, ‘cut’, ‘demand’, ‘lead’, ‘population’, ‘routing’, ‘instrumental’, ‘great’] | [‘bibliometrics’, ‘bibliometric’, ‘scientometrics’, ‘classification’, ‘chemometrics’, ‘categorization’, ‘citation’, ‘chemometric’, ‘machinelearningbased’, ‘networksbased’] | [‘neural’, ‘chemometrics’, ‘metamethodology’, ‘bibliometrics’, ‘classification’, ‘scientometrics’, ‘neurofuzzy’, ‘decisionsupportsystem’, ‘machinelearningbased’, ‘citation’] | |
Bibliometric and Information Retrieval Impact Analysis | 11 | 37 | Machine Learning for Information Retrieval and Citation Analysis in Medical Research | 11_database_search_recall_medline | [‘database’, ‘search’, ‘recall’, ‘medline’, ‘bibliographic’, ‘precision’, ‘retrieval’, ‘federated’, ‘chemical’, ‘heading’, ‘subject’, ‘systematic’, ‘medical’, ‘strategy’, ‘literature’, ‘pubmed’, ‘searching’, ‘controlled’, ‘review’, ‘randomized’, ‘embase’, ‘information’, ‘care’, ‘vocabulary’, ‘mesh’, ‘trial’, ‘health’, ‘study’, ‘rate’, ‘data’, ‘learning’, ‘identifying’, ‘controlledtrials’, ‘substance’, ‘thesaurus’, ‘hemorrhage’, ‘survival’, ‘multiinstitutional’, ‘machine’, ‘best’, ‘medicine’, ‘deep’, ‘semisupervised’, ‘evidencebased’, ‘crowdsourcing’, ‘clinical’, ‘area’, ‘accuracy’, ‘record’, ‘model’, ‘test’, ‘inspec’, ‘toxicological’, ‘uncontrolled’, ‘psychosocial’, ‘curation’, ‘congenital’, ‘occupationalhealth’, ‘prostate’, ‘omop’, ‘intracerebral’, ‘communityengaged’, ‘expansion’, ‘prognosis’, ‘hypothyroidism’, ‘lilac’, ‘musculoskeletal’, ‘decision’, ‘abstract’, ‘biomedical’, ‘gpt4’, ‘augmentation’, ‘risk’, ‘evidence’, ‘representation’, ‘support’, ‘selected’, ‘transformerbased’, ‘query’, ‘guideline’, ‘relevant’, ‘performance’, ‘confidence’, ‘open’, ‘collaboration’, ‘evaluation’, ‘outcome’, ‘informatics’, ‘patient’, ‘improving’, ‘stroke’, ‘validation’, ‘synthesis’, ‘access’, ‘cancer’, ‘common’, ‘transfer’, ‘engine’, ‘statistic’, ‘critical’] | [‘pubmed’, ‘medline’, ‘search’, ‘database’, ‘retrieval’, ‘searching’, ‘embase’, ‘systematic’, ‘bibliographic’, ‘review’] | [‘search’, ‘medline’, ‘pubmed’, ‘embase’, ‘mesh’, ‘identifying’, ‘thesaurus’, ‘semisupervised’, ‘crowdsourcing’, ‘communityengaged’] | |
Bibliometric Analysis of Deep Learning and Machine Learning Technologies in Various Domains | 29 | 13 | Machine Learning for Bibliometric Analysis and Research Impact Prediction | 29_deep_disease_object_bibliometric | [‘deep’, ‘disease’, ‘object’, ‘bibliometric’, ‘screening’, ‘fraud’, ‘kidney’, ‘credit’, ‘learning’, ‘resistance’, ‘card’, ‘convolutional’, ‘vision’, ‘detection’, ‘classification’, ‘rating’, ‘microsimulation’, ‘chronic’, ‘antimicrobial’, ‘leaf’, ‘computer’, ‘machine’, ‘literature’, ‘3d’, ‘analysis’, ‘agency’, ‘fulltext’, ‘bibliometricenhanced’, ‘ensemble’, ‘systematic’, ‘lstm’, ‘cancer’, ‘orientation’, ‘neural’, ‘algorithm’, ‘application’, ‘automatic’, ‘vosviewer’, ‘review’, ‘economics’, ‘transaction’, ‘nephropathy’, ‘renaldisease’, ‘mitosis’, ‘iga’, ‘faultdiagnosis’, ‘functionbased’, ‘glomerularfiltrationrate’, ‘gradebased’, ‘skincancer’, ‘exclusively’, ‘progression’, ‘costeffectiveness’, ‘20142024’, ‘ckd’, ‘visualizationbased’, ‘antibiotic’, ‘20072019’, ‘occurs’, ‘occf’, ‘recognition’, ‘text’, ‘decline’, ‘bond’, ‘2015’, ‘accountable’, ‘qualityoflife’, ‘lungcancer’, ‘retrieval’, ‘intelligent’, ‘analytics’, ‘stage’, ‘population’, ‘risk’, ‘health’, ‘future’, ‘online’, ‘model’, ‘network’, ‘bidirectional’, ‘leveraging’, ‘bibliometrics’, ‘biblioshiny’, ‘2023’, ‘present’, ‘imaging’, ‘hot’, ‘era’, ‘index’, ‘governance’, ‘searching’, ‘cost’, ‘past’, ‘data’, ‘architecture’, ‘semantics’, ‘neuralnetwork’, ‘recent’, ‘attention’, ‘novel’] | [‘classification’, ‘bibliometrics’, ‘review’, ‘bibliometric’, ‘convolutional’, ‘bibliometricenhanced’, ‘systematic’, ‘fulltext’, ‘neuralnetwork’, ‘neural’] | [‘convolutional’, ‘classification’, ‘bibliometricenhanced’, ‘review’, ‘skincancer’, ‘ckd’, ‘analytics’, ‘leveraging’, ‘bibliometrics’, ‘neuralnetwork’] | |
Bibliometric and Scientometric Trends in ML/AI across Diverse Domains | 22 | 18 | Artificial Intelligence for Autism Spectrum Disorder Research | 22_robot_safety_disorder_military | [‘robot’, ‘safety’, ‘disorder’, ‘military’, ‘trend’, ‘stroke’, ‘autism’, ‘mastitis’, ‘intelligence’, ‘bibliometric’, ‘artificial’, ‘spectrum’, ‘rehabilitation’, ‘machine’, ‘gait’, ‘glove’, ‘global’, ‘hotspot’, ‘interaction’, ‘analysis’, ‘ai’, ‘poststroke’, ‘cow’, ‘defence’, ‘milk’, ‘learning’, ‘cuttingedge’, ‘security’, ‘sensor’, ‘depression’, ‘research’, ‘visualized’, ‘robotics’, ‘road’, ‘movement’, ‘child’, ‘operation’, ‘technology’, ‘transportation’, ‘metaanalysis’, ‘test’, ‘precision’, ‘monitoring’, ‘citespace’, ‘national’, ‘state’, ‘disease’, ‘data’, ‘survey’, ‘application’, ‘bibliometrics’, ‘ligament’, ‘pathological’, ‘svc’, ‘migraine’, ‘parkinsonsdisease’, ‘radiologyrelated’, ‘grasp’, ‘psychiatric’, ‘subclinical’, ‘1992’, ‘riskfactors’, ‘robotic’, ‘thumb’, ‘farm’, ‘exoskeleton’, ‘wearable’, ‘runtime’, ‘dairycattle’, ‘culturaldifferences’, ‘biomarkers’, ‘cruciate’, ‘accelerometer’, ‘arat’, ‘dairy’, ‘cortical’, ‘walking’, ‘depressive’, ‘cerebralpalsy’, ‘depolarization’, ‘bovine’, ‘block’, ‘bipolar’, ‘natural’, ‘processing’, ‘service’, ‘technique’, ‘identification’, ‘medical’, ‘roc’, ‘anterior’, ‘arm’, ‘disability’, ‘spreading’, ‘condition’, ‘theoretical’, ‘humancentered’, ‘intelligent’, ‘connectivity’, ‘virtualreality’] | [‘bibliometric’, ‘bibliometrics’, ‘survey’, ‘metaanalysis’, ‘robotic’, ‘ai’, ‘research’, ‘robot’, ‘citespace’, ‘robotics’] | [‘safety’, ‘gait’, ‘ai’, ‘poststroke’, ‘research’, ‘parkinsonsdisease’, ‘robotic’, ‘exoskeleton’, ‘arm’, ‘disability’] | |
Machine Learning and Artificial Intelligence for Bibliometric Analysis | ML/AI-Driven Bibliometrics and Research Impact Assessment15 | 14 | 31 | Machine Learning for Research Impact Analysis | 14_machine_impact_peer_paper | [‘machine’, ‘impact’, ‘peer’, ‘paper’, ‘highly’, ‘citation’, ‘indicator’, ‘cited’, ‘count’, ‘learning’, ‘exercise’, ‘review’, ‘quality’, ‘article’, ‘journal’, ‘readability’, ‘feature’, ‘publication’, ‘research’, ‘bibliometrics’, ‘funding’, ‘textual’, ‘scientometrics’, ‘national’, ‘productivity’, ‘academic’, ‘finance’, ‘selection’, ‘ranking’, ‘importance’, ‘excellence’, ‘bias’, ‘cost’, ‘science’, ‘institute’, ‘predicting’, ‘behavior’, ‘predict’, ‘basin’, ‘pacific’, ‘blood’, ‘algorithmic’, ‘lung’, ‘excellent’, ‘decision’, ‘data’, ‘transparency’, ‘reader’, ‘disclosure’, ‘assessment’, ‘uk’, ‘highlycited’, ‘machinelearning’, ‘imbalanced’, ‘sleeping’, ‘beauty’, ‘heart’, ‘informetrics’, ‘bibliometric’, ‘accounting’, ‘alternative’, ‘assisted’, ‘perspective’, ‘institution’, ‘svm’, ‘metric’, ‘criterion’, ‘radiology’, ‘scientific’, ‘number’, ‘performance’, ‘evaluation’, ‘rating’, ‘intelligence’, ‘improve’, ‘book’, ‘characteristic’, ‘field’, ‘determinant’, ‘abstract’, ‘prediction’, ‘insight’, ‘forest’, ‘analysis’, ‘methodology’, ‘disambiguation’, ‘index’, ‘random’, ‘topic’, ‘handelsblatt’, ‘oa’, ‘oxygenuptake’, ‘habilitation’, ‘glmlss’, ‘fitness’, ‘o2’, ‘realestate’, ‘gini’, ‘highintensity’, ‘matthew’] | [‘scientometrics’, ‘bibliometric’, ‘bibliometrics’, ‘informetrics’, ‘citation’, ‘cited’, ‘ranking’, ‘highlycited’, ‘publication’, ‘research’] | [‘citation’, ‘review’, ‘readability’, ‘bibliometrics’, ‘scientometrics’, ‘ranking’, ‘predict’, ‘machinelearning’, ‘informetrics’, ‘bibliometric’] |
ML/AI-Enhanced Bibliometric Analysis and Publication Impact Evaluation | 15 | 31 | Artificial Intelligence for Scientific Collaboration and Citation Impact Analysis | 15_artificial_intelligence_collaboration_journal | [‘artificial’, ‘intelligence’, ‘collaboration’, ‘journal’, ‘citation’, ‘impact’, ‘international’, ‘ranking’, ‘hindex’, ‘pattern’, ‘business’, ‘ai’, ‘paper’, ‘pagerank’, ‘publication’, ‘isi’, ‘science’, ‘index’, ‘proceeding’, ‘helix’, ‘institution’, ‘global’, ‘institutional’, ‘case’, ‘computerscience’, ‘quality’, ‘research’, ‘google’, ‘scientific’, ‘productivity’, ‘level’, ‘perplexity’, ‘agglomeration’, ‘pasteur’, ‘quadrant’, ‘hcindex’, ‘coordinated’, ‘gergm’, ‘asia’, ‘network’, ‘national’, ‘performance’, ‘computer’, ‘innovation’, ‘counting’, ‘gindex’, ‘triple’, ‘trend’, ‘analysis’, ‘novelty’, ‘russian’, ‘researcher’, ‘china’, ‘collaborative’, ‘reference’, ‘combination’, ‘comparing’, ‘academic’, ‘scholarly’, ‘conditional’, ‘leadership’, ‘development’, ‘scientist’, ‘world’, ‘competition’, ‘based’, ‘approach’, ‘factor’, ‘economy’, ‘conference’, ‘field’, ‘scholar’, ‘evaluating’, ‘study’, ‘environmental’, ‘measure’, ‘domain’, ‘article’, ‘perception’, ‘data’, ‘scopus’, ‘survey’, ‘coauthorship’, ‘design’, ‘thematical’, ‘uzzi’, ‘managementi’, ‘fellowship’, ‘mostcited’, ‘atypical’, ‘authoraffiliationindex’, ‘parsimonious’, ‘morphology’, ‘form’, ‘1985’, ‘patentcited’, ‘topicsensitivity’, ‘independency’, ‘citerbased’, ‘ntuple’] | [‘ranking’, ‘citation’, ‘institution’, ‘pagerank’, ‘scopus’, ‘coauthorship’, ‘scholarly’, ‘isi’, ‘institutional’, ‘authoraffiliationindex’] | [‘citation’, ‘ranking’, ‘ai’, ‘pagerank’, ‘isi’, ‘index’, ‘conference’, ‘scopus’, ‘coauthorship’, ‘authoraffiliationindex’] | |
Machine Learning and Artificial Intelligence for Specific Dimension of Research Impact | ML/AI-driven Evaluation Metrics and Models for Research Performance and Innovation Assessment | 5 | 51 | Machine Learning for Research Impact Analysis | 5_project_evaluation_based_risk | [‘project’, ‘evaluation’, ‘based’, ‘risk’, ‘neural’, ‘performance’, ‘principal’, ‘research’, ‘component’, ‘method’, ‘network’, ‘safety’, ‘enterprise’, ‘selection’, ‘svm’, ‘management’, ‘model’, ‘deep’, ‘grey’, ‘assessment’, ‘comprehensive’, ‘manifold’, ‘sparse’, ‘hierarchy’, ‘linear’, ‘prediction’, ‘learning’, ‘universityindustry’, ‘algorithm’, ‘theory’, ‘error’, ‘analytic’, ‘matrix’, ‘wavelet’, ‘entropy’, ‘technology’, ‘human’, ‘regression’, ‘analysis’, ‘traffic’, ‘propagation’, ‘data’, ‘process’, ‘weighted’, ‘metric’, ‘investment’, ‘outward’, ‘underground’, ‘microwave’, ‘baijiu’, ‘truck’, ‘overrun’, ‘centrifugal’, ‘rtd’, ‘compressor’, ‘multiplier’, ‘stickslip’, ‘pose’, ‘straightness’, ‘consistency’, ‘openpit’, ‘tacit’, ‘phm’, ‘armored’, ‘uniformity’, ‘evidential’, ‘flavor’, ‘committime’, ‘sensory’, ‘passthrough’, ‘evacuation’, ‘intelligent’, ‘statistical’, ‘empirical’, ‘artificial’, ‘machine’, ‘innovation’, ‘exchange’, ‘loading’, ‘accident’, ‘voltage’, ‘fund’, ‘spss’, ‘black’, ‘equal’, ‘forecast’, ‘reasoning’, ‘construction’, ‘rate’, ‘hydrostatic’, ‘recurrent’, ‘supplier’, ‘heating’, ‘food’, ‘driving’, ‘vibration’, ‘crossvalidation’, ‘direct’, ‘rough’, ‘output’] | [‘weighted’, ‘evaluation’, ‘project’, ‘crossvalidation’, ‘svm’, ‘empirical’, ‘research’, ‘spss’, ‘assessment’, ‘method’] | [‘project’, ‘risk’, ‘neural’, ‘svm’, ‘algorithm’, ‘wavelet’, ‘weighted’, ‘truck’, ‘spss’, ‘crossvalidation’] |
Sentiment and Citation Impact Analysis through Machine Learning Techniques | 6 | 48 | Citation Analysis and Sentiment Measurement in Scientific Research | 6_sentiment_citation_analysis_classification | [‘sentiment’, ‘citation’, ‘analysis’, ‘classification’, ‘opinion’, ‘scientific’, ‘multitask’, ‘impact’, ‘feature’, ‘intext’, ‘paper’, ‘negative’, ‘mining’, ‘emotion’, ‘ontology’, ‘index’, ‘advertising’, ‘important’, ‘science’, ‘linguistic’, ‘context’, ‘author’, ‘article’, ‘ngram’, ‘good’, ‘factor’, ‘text’, ‘machine’, ‘intent’, ‘reason’, ‘smote’, ‘language’, ‘frequency’, ‘identification’, ‘polarity’, ‘processing’, ‘learning’, ‘approach’, ‘evaluation’, ‘using’, ‘datasets’, ‘knn’, ‘ranking’, ‘natural’, ‘publication’, ‘technique’, ‘vector’, ‘textual’, ‘binary’, ‘quality’, ‘recommendation’, ‘term’, ‘ccro’, ‘nlpbased’, ‘f1000prime’, ‘ngrams’, ‘postpublication’, ‘disagreement’, ‘gst’, ‘positivity’, ‘meaningful’, ‘variation’, ‘serbian’, ‘10k’, ‘sentiwordnet’, ‘retrieval’, ‘extraction’, ‘search’, ‘contextbased’, ‘tackle’, ‘authoritative’, ‘aspect’, ‘tax’, ‘reproducible’, ‘usefulness’, ‘cited’, ‘model’, ‘support’, ‘mapping’, ‘forest’, ‘span’, ‘determining’, ‘summarisation’, ‘wos’, ‘comment’, ‘tfidf’, ‘research’, ‘random’, ‘consumer’, ‘preliminary’, ‘semantic’, ‘semisupervised’, ‘multilayer’, ‘study’, ‘product’, ‘linguistics’, ‘disciplinary’, ‘communication’, ‘profiling’, ‘weight’] | [‘citation’, ‘nlpbased’, ‘cited’, ‘ranking’, ‘classification’, ‘impact’, ‘publication’, ‘evaluation’, ‘postpublication’, ‘polarity’] | [‘citation’, ‘classification’, ‘impact’, ‘polarity’, ‘using’, ‘ranking’, ‘nlpbased’, ‘ngrams’, ‘postpublication’, ‘sentiwordnet’] | |
Predictive Modelling of Citation Impact and Research Metrics | 12 | 34 | Citation Prediction and Impact Analysis in Academic Research | 12_count_citation_prediction_impact | [‘count’, ‘citation’, ‘prediction’, ‘impact’, ‘deep’, ‘network’, ‘feature’, ‘paper’, ‘journal’, ‘learning’, ‘neural’, ‘predicting’, ‘bert’, ‘using’, ‘scientific’, ‘graph’, ‘acknowledgement’, ‘factor’, ‘semantic’, ‘index’, ‘hindex’, ‘machine’, ‘academic’, ‘series’, ‘article’, ‘text’, ‘classification’, ‘ranking’, ‘analysis’, ‘temporal’, ‘publication’, ‘rule’, ‘time’, ‘dataset’, ‘boundaryspanning’, ‘burst’, ‘wlsa’, ‘anomalous’, ‘junior’, ‘missing’, ‘guidance’, ‘citescore’, ‘imputation’, ‘advance’, ‘span’, ‘summarisation’, ‘award’, ‘score’, ‘forecasting’, ‘shortterm’, ‘document’, ‘scholarly’, ‘popularity’, ‘variant’, ‘context’, ‘long’, ‘title’, ‘cnn’, ‘multivariate’, ‘scheme’, ‘contribution’, ‘memory’, ‘selection’, ‘weighted’, ‘detection’, ‘influential’, ‘future’, ‘knowledge’, ‘model’, ‘term’, ‘visual’, ‘national’, ‘function’, ‘abstract’, ‘value’, ‘link’, ‘cited’, ‘representation’, ‘convolutional’, ‘metadata’, ‘scientometrics’, ‘role’, ‘based’, ‘regression’, ‘researcher’, ‘finetuning’, ‘annotator’, ‘knni’, ‘affecting’, ‘lm’, ‘formulation’, ‘fox’, ‘ibro’, ‘an’, ‘topicscore’, ‘inflation’, ‘am’, ‘fundamental’, ‘frequencyinverse’, ‘aps’] | [‘scientometrics’, ‘citation’, ‘cited’, ‘classification’, ‘predicting’, ‘weighted’, ‘ranking’, ‘scholarly’, ‘publication’, ‘convolutional’] | [‘citation’, ‘neural’, ‘predicting’, ‘bert’, ‘classification’, ‘ranking’, ‘citescore’, ‘scientometrics’, ‘annotator’, ‘topicscore’] | |
ML/AI in Research Evaluation and Methodology | 13 | 31 | Machine Learning for Domestic Violence Policing | 13_policing_violence_qualitative_domestic | [‘policing’, ‘violence’, ‘qualitative’, ‘domestic’, ‘organizational’, ‘research’, ‘reporting’, ‘tool’, ‘machine’, ‘humanai’, ‘clinical’, ‘inquiry’, ‘evaluation’, ‘screening’, ‘appreciative’, ‘patrol’, ‘natural’, ‘usability’, ‘order’, ‘language’, ‘criterion’, ‘classification’, ‘measurement’, ‘collaboration’, ‘nlp’, ‘processing’, ‘learning’, ‘abuse’, ‘seamless’, ‘meter’, ‘authoring’, ‘eligibility’, ‘checklist’, ‘posttraumatic’, ‘prescreening’, ‘starml’, ‘foot’, ‘performance’, ‘evaluating’, ‘family’, ‘adversarial’, ‘welfare’, ‘phone’, ‘assessment’, ‘versus’, ‘sensemaking’, ‘portfolio’, ‘automation’, ‘inclusion’, ‘methodology’, ‘leveraging’, ‘scoring’, ‘knowledge’, ‘ai’, ‘text’, ‘justice’, ‘extension’, ‘classifying’, ‘crowdsourcing’, ‘stress’, ‘child’, ‘translational’, ‘social’, ‘reading’, ‘identification’, ‘transformer’, ‘using’, ‘case’, ‘focus’, ‘example’, ‘intelligent’, ‘potential’, ‘disorder’, ‘transfer’, ‘diversity’, ‘community’, ‘change’, ‘program’, ‘translation’, ‘record’, ‘discovery’, ‘task’, ‘authorship’, ‘platform’, ‘action’, ‘abstract’, ‘mobile’, ‘question’, ‘science’, ‘supervised’, ‘high’, ‘overview’, ‘open’, ‘decisionmaking’, ‘quality’, ‘domain’, ‘perception’, ‘work’, ‘data’, ‘human’] | [‘classifying’, ‘classification’, ‘methodology’, ‘qualitative’, ‘research’, ‘evaluation’, ‘assessment’, ‘crowdsourcing’, ‘evaluating’, ‘nlp’] | [‘policing’, ‘qualitative’, ‘tool’, ‘humanai’, ‘nlp’, ‘posttraumatic’, ‘sensemaking’, ‘ai’, ‘classifying’, ‘crowdsourcing’] | |
Impact of Deep Learning and Machine Learning on Research Collaboration Prediction and Network Analysis | 31 | 13 | Machine Learning for Collaboration and Citation Prediction in Academic Research | 31_link_collaboration_coauthorship_network | [‘link’, ‘collaboration’, ‘coauthorship’, ‘network’, ‘prediction’, ‘representation’, ‘elm’, ‘layer’, ‘autoencoder’, ‘hidden’, ‘recommender’, ‘learning’, ‘recommendation’, ‘topn’, ‘double’, ‘delmae’, ‘myelopathy’, ‘original’, ‘spatialtemporal’, ‘hierarchical’, ‘future’, ‘expressive’, ‘denoising’, ‘random’, ‘input’, ‘extreme’, ‘feature’, ‘predicting’, ‘multilayer’, ‘machine’, ‘deep’, ‘system’, ‘pattern’, ‘centrality’, ‘novel’, ‘research’, ‘author’, ‘supervised’, ‘evolution’, ‘training’, ‘collaborative’, ‘attentionbased’, ‘spondylotic’, ‘shall’, ‘architectural’, ‘helm’, ‘proximityaware’, ‘randomwalk’, ‘hdelm’, ‘restricted’, ‘similaritybased’, ‘decompression’, ‘degenerative’, ‘multinetwork’, ‘ratingtrend’, ‘nodal’, ‘closeness’, ‘fast’, ‘extremely’, ‘linkprediction’, ‘compact’, ‘autoencoders’, ‘cervical’, ‘incorporating’, ‘graphbased’, ‘similarity’, ‘approach’, ‘speed’, ‘decoding’, ‘discriminantanalysis’, ‘surgical’, ‘stochastic’, ‘graph’, ‘lead’, ‘description’, ‘attribute’, ‘encoding’, ‘factorization’, ‘scientific’, ‘machinelearning’, ‘interest’, ‘affiliation’, ‘signature’, ‘stacking’, ‘relevant’, ‘embeddings’, ‘neighbor’, ‘maximization’, ‘filtering’, ‘kernel’, ‘ecommerce’, ‘noise’, ‘matrix’, ‘coauthor’, ‘used’, ‘reduction’, ‘different’, ‘cooccurrence’, ‘capacity’, ‘leadership’] | [‘linkprediction’, ‘graphbased’, ‘similaritybased’, ‘coauthorship’, ‘embeddings’, ‘centrality’, ‘autoencoder’, ‘network’, ‘coauthor’, ‘autoencoders’] | [‘link’, ‘coauthorship’, ‘network’, ‘autoencoder’, ‘recommender’, ‘centrality’, ‘similaritybased’, ‘linkprediction’, ‘graphbased’, ‘embeddings’] | |
Impact of Deep Learning and Machine Learning on Citation Analysis and Recommender Systems | 30 | 13 | Machine Learning for Research Impact Analysis | 30_recommender_system_citation_context | [‘recommender’, ‘system’, ‘citation’, ‘context’, ‘recommendation’, ‘scientific’, ‘filtering’, ‘deep’, ‘summarization’, ‘discourse’, ‘paper’, ‘facet’, ‘multitopic’, ‘k12’, ‘learning’, ‘personalized’, ‘patent’, ‘pagerank’, ‘proximity’, ‘flow’, ‘semantics’, ‘analysis’, ‘measuring’, ‘influential’, ‘knowledge’, ‘coupling’, ‘elearning’, ‘representation’, ‘using’, ‘article’, ‘survey’, ‘news’, ‘trend’, ‘collaborative’, ‘ontological’, ‘contextualization’, ‘suggester’, ‘serendipity’, ‘informative’, ‘serendipitous’, ‘authorprofilebased’, ‘userprofile’, ‘bibliographic’, ‘similarity’, ‘natural’, ‘document’, ‘processing’, ‘market’, ‘recommending’, ‘kernelbased’, ‘implicit’, ‘light’, ‘candidate’, ‘managing’, ‘classification’, ‘neural’, ‘challenge’, ‘community’, ‘distributed’, ‘dbscan’, ‘modified’, ‘venue’, ‘specialty’, ‘machinelearning’, ‘recurrent’, ‘language’, ‘short’, ‘selforganizing’, ‘networkbased’, ‘academic’, ‘preference’, ‘datasets’, ‘investigating’, ‘long’, ‘machine’, ‘space’, ‘informationscience’, ‘network’, ‘memory’, ‘statistic’, ‘mining’, ‘novel’, ‘understanding’, ‘feedback’, ‘term’, ‘diffusion’, ‘management’, ‘journal’, ‘abstract’, ‘empirical’, ‘insight’, ‘comprehensive’, ‘map’, ‘hybrid’, ‘role’, ‘bibliometrics’, ‘economics’, ‘use’, ‘user’, ‘semantic’] | [‘recommender’, ‘suggester’, ‘machinelearning’, ‘neural’, ‘survey’, ‘recommendation’, ‘informationscience’, ‘pagerank’, ‘classification’, ‘bibliometrics’] | [‘citation’, ‘pagerank’, ‘contextualization’, ‘suggester’, ‘authorprofilebased’, ‘neural’, ‘dbscan’, ‘networkbased’, ‘informationscience’, ‘bibliometrics’] | |
Impact and Innovation in Bibliographic Data Extraction and Analysis | 8 | 44 | Machine Learning for Bibliographic Disambiguation and Author Disambiguation | 8_bibliographic_disambiguation_library_reference | [‘bibliographic’, ‘disambiguation’, ‘library’, ‘reference’, ‘digital’, ‘entity’, ‘metadata’, ‘extraction’, ‘author’, ‘book’, ‘record’, ‘information’, ‘machine’, ‘document’, ‘workshop’, ‘data’, ‘parsing’, ‘loan’, ‘birndl’, ‘retrieval’, ‘format’, ‘conditional’, ‘name’, ‘joint’, ‘bibliometricenhanced’, ‘language’, ‘random’, ‘parser’, ‘detection’, ‘deep’, ‘linkage’, ‘vector’, ‘learning’, ‘named’, ‘linking’, ‘processing’, ‘image’, ‘resolution’, ‘using’, ‘network’, ‘neural’, ‘support’, ‘natural’, ‘nlp’, ‘history’, ‘recommendation’, ‘server’, ‘equivalence’, ‘linked’, ‘bibframe’, ‘cip’, ‘commentary’, ‘subjectclassification’, ‘html’, ‘rdf’, ‘hyperdocument’, ‘based’, ‘coupling’, ‘hierarchical’, ‘authorship’, ‘layout’, ‘description’, ‘field’, ‘publication’, ‘century’, ‘approximate’, ‘bibliography’, ‘opensource’, ‘dblp’, ‘clustering’, ‘citation’, ‘historical’, ‘similarity’, ‘recognition’, ‘semantic’, ‘object’, ‘authority’, ‘summarization’, ‘benchmarking’, ‘svm’, ‘standard’, ‘type’, ‘validation’, ‘source’, ‘scheme’, ‘identity’, ‘electronic’, ‘improvement’, ‘computer’, ‘categorization’, ‘architecture’, ‘tool’, ‘classification’, ‘web’, ‘chinese’, ‘science’, ‘convolutional’, ‘recommender’, ‘work’, ‘map’] | [‘bibliometricenhanced’, ‘bibframe’, ‘subjectclassification’, ‘rdf’, ‘library’, ‘reference’, ‘classification’, ‘citation’, ‘nlp’, ‘bibliography’] | [‘bibliographic’, ‘disambiguation’, ‘library’, ‘bibliometricenhanced’, ‘linkage’, ‘bibframe’, ‘subjectclassification’, ‘rdf’, ‘hyperdocument’, ‘dblp’] | |
Impact of Proximity Dimensions and Topic Modelling on International Research Collaboration | 33 | 11 | Digital Native and Immigrant Research Collaboration | 33_nurse_immigrant_international_dimension | [‘nurse’, ‘immigrant’, ‘international’, ‘dimension’, ‘proximity’, ‘turnover’, ‘journalism’, ‘job’, ‘mobility’, ‘andalusian’, ‘citizen’, ‘employee’, ‘topic’, ‘modeling’, ‘native’, ‘researcher’, ‘collaboration’, ‘talent’, ‘network’, ‘complex’, ‘integration’, ‘digital’, ‘structural’, ‘satisfaction’, ‘using’, ‘regression’, ‘distance’, ‘bibliometrics’, ‘myth’, ‘newsroom’, ‘occupationalmobility’, ‘r12’, ‘registered’, ‘dissatisfaction’, ‘spillover’, ‘sixtytwo’, ‘hyptrails’, ‘immigration’, ‘informationseeking’, ‘impactable’, ‘intergenerational’, ‘migration’, ‘greatbritain’, ‘geometry’, ‘coinventorships’, ‘antecedent’, ‘ethnic’, ‘localization’, ‘explain’, ‘geography’, ‘19942023’, ‘staffing’, ‘content’, ‘outcome’, ‘linear’, ‘analysis’, ‘bayesian’, ‘mortality’, ‘manual’, ‘migrant’, ‘o31’, ‘korean’, ‘coauthorships’, ‘register’, ‘revisiting’, ‘youth’, ‘dimensionality’, ‘databased’, ‘empiricalevidence’, ‘social’, ‘divide’, ‘earnings’, ‘german’, ‘embeddedness’, ‘modelingbased’, ‘health’, ‘database’, ‘medium’, ‘bibliometric’, ‘university’, ‘single’, ‘net’, ‘initiative’, ‘usergenerated’, ‘aid’, ‘structured’, ‘programme’, ‘multidisciplinary’, ‘pilot’, ‘dimensionsai’, ‘unitedstates’, ‘predictor’, ‘prospect’, ‘concrete’, ‘present’, ‘cooperation’, ‘individual’, ‘reduction’, ‘emergence’, ‘augmented’] | [‘bibliometrics’, ‘bibliometric’, ‘structured’, ‘embeddedness’, ‘antecedent’, ‘impactable’, ‘researcher’, ‘multidisciplinary’, ‘databased’, ‘complex’] | [‘proximity’, ‘network’, ‘bibliometrics’, ‘occupationalmobility’, ‘impactable’, ‘migration’, ‘coauthorships’, ‘dimensionality’, ‘databased’, ‘embeddedness’] | |
Advanced Techniques in Bibliometric and Scientometric Analysis for Understanding Research Impact and Collaboration | 23 | 18 | Gender and Impact of Scholarly Research | 23_gender_quotient_information_newspaper | [‘gender’, ‘quotient’, ‘information’, ‘newspaper’, ‘nonlocal’, ‘faculty’, ‘journal’, ‘internationality’, ‘productivity’, ‘doe’, ‘influence’, ‘processing’, ‘academic’, ‘rd’, ‘sourcenormalized’, ‘ocq’, ‘nliq’, ‘research’, ‘impact’, ‘collaboration’, ‘matter’, ‘natural’, ‘scientific’, ‘multidimensional’, ‘scraping’, ‘language’, ‘genderdifferences’, ‘blog’, ‘american’, ‘style’, ‘snip’, ‘management’, ‘sex’, ‘affect’, ‘data’, ‘outcome’, ‘gap’, ‘cooperation’, ‘international’, ‘visualization’, ‘social’, ‘background’, ‘performance’, ‘modeling’, ‘diversity’, ‘citation’, ‘determinant’, ‘web’, ‘function’, ‘supervised’, ‘writing’, ‘structural’, ‘article’, ‘news’, ‘word’, ‘topic’, ‘collaborator’, ‘ugnn’, ‘russia’, ‘refinitiv’, ‘latin’, ‘bertbased’, ‘soviet’, ‘replicability’, ‘journalist’, ‘stringmatching’, ‘scientobase’, ‘idiindex’, ‘metaphilosophy’, ‘female’, ‘jimi’, ‘fi’, ‘machinereadable’, ‘lected’, ‘knowledgesharing’, ‘wisdom’, ‘eld’, ‘informationsources’, ‘thomson’, ‘easy’, ‘selfpromotion’, ‘researchmethods’, ‘gatekeeping’, ‘microservices’, ‘chilean’, ‘chile’, ‘20082018’, ‘roduction’, ‘granular’, ‘builtin’, ‘philosophical’, ‘press’, ‘rhetorical’, ‘reuters’, ‘cobbdouglas’, ‘segregation’, ‘pyrolysis’, ‘said’, ‘descent’, ‘doctrine’] | [‘gender’, ‘researchmethods’, ‘citation’, ‘genderdifferences’, ‘impact’, ‘informationsources’, ‘academic’, ‘research’, ‘collaborator’, ‘multidimensional’] | [‘gender’, ‘impact’, ‘multidimensional’, ‘scraping’, ‘collaborator’, ‘bertbased’, ‘idiindex’, ‘knowledgesharing’, ‘informationsources’, ‘researchmethods’] | |
Machine Learning and Statistical Methods for Research Evaluation and Performance Assessment | 34 | 10 | Machine Learning for Research Impact Analysis | 34_svm_evaluation_normalization_parallel | [‘svm’, ‘evaluation’, ‘normalization’, ‘parallel’, ‘bp’, ‘vocational’, ‘application’, ‘algorithm’, ‘discipline’, ‘project’, ‘research’, ‘set’, ‘large’, ‘college’, ‘clinical’, ‘based’, ‘hownet’, ‘poverty’, ‘fourier’, ‘fourierkernel’, ‘fcm’, ‘alleviation’, ‘environment’, ‘computing’, ‘vector’, ‘photovoltaic’, ‘grade’, ‘performance’, ‘extraction’, ‘scientific’, ‘post’, ‘supplier’, ‘kernel’, ‘subjective’, ‘feature’, ‘multilayer’, ‘benefit’, ‘machine’, ‘index’, ‘space’, ‘development’, ‘regression’, ‘scheme’, ‘classifier’, ‘data’, ‘improve’, ‘student’, ‘credit’, ‘comparison’, ‘question’, ‘function’, ‘chinese’, ‘applied’, ‘automated’, ‘assessment’, ‘comprehensive’, ‘tree’, ‘similarity’, ‘semantic’, ‘decision’, ‘support’, ‘big’, ‘learning’, ‘method’, ‘study’, ‘model’] | [‘svm’, ‘classifier’] | [‘svm’, ‘evaluation’, ‘normalization’, ‘algorithm’, ‘hownet’, ‘vector’, ‘kernel’, ‘classifier’, ‘applied’] | |
Machine Learning, Artificial Intelligence and Advance Methodologies for Research Impact Applications | Advanced Evaluation Models and Algorithms in Educational, Environmental, and Market Research | 24 | 17 | Research Evaluation and Machine Learning | 24_evaluation_kmeans_english_based | [‘evaluation’, ‘kmeans’, ‘english’, ‘based’, ‘teaching’, ‘clustering’, ‘model’, ‘platform’, ‘segmentation’, ‘boosting’, ‘tree’, ‘vision’, ‘power’, ‘mining’, ‘service’, ‘vector’, ‘eggshell’, ‘b2c’, ‘marking’, ‘wuqing’, ‘express’, ‘dark’, ‘crossborder’, ‘servqual’, ‘secondhand’, ‘belt’, ‘morality’, ‘couplet’, ‘decision’, ‘college’, ‘dbscan’, ‘image’, ‘algorithm’, ‘support’, ‘point’, ‘completeness’, ‘teacher’, ‘research’, ‘machine’, ‘tire’, ‘spot’, ‘sequence’, ‘coefficient’, ‘ecommerce’, ‘quality’, ‘diagram’, ‘svm’, ‘market’, ‘defect’, ‘foreign’, ‘ability’, ‘price’, ‘climate’, ‘strategic’, ‘data’, ‘business’, ‘adaptive’, ‘credit’, ‘translation’, ‘method’, ‘sustainability’, ‘regression’, ‘commodity’, ‘gbdt’, ‘duty’, ‘penetration’, ‘overseas’, ‘contour’, ‘boruta’, ‘mechine’, ‘salmonella’, ‘dex’, ‘svr’, ‘politics’, ‘car’, ‘ideological’, ‘densitybased’, ‘nadaboost’, ‘silhouette’, ‘svmbased’, ‘user’, ‘semantic’, ‘student’, ‘oriented’, ‘solution’, ‘databased’, ‘crack’, ‘manual’, ‘ideology’, ‘lighting’, ‘university’, ‘gradient’, ‘cycle’, ‘political’, ‘customer’, ‘digital’, ‘learning’, ‘logistics’, ‘road’, ‘big’] | [‘svm’, ‘kmeans’, ‘algorithm’, ‘clustering’, ‘evaluation’, ‘dbscan’, ‘method’, ‘segmentation’, ‘boosting’, ‘databased’] | [‘evaluation’, ‘kmeans’, ‘clustering’, ‘boosting’, ‘vector’, ‘dbscan’, ‘algorithm’, ‘ecommerce’, ‘svm’, ‘databased’] |
Bibliometric and AI-Enhanced Analysis of Sustainable Development and Technological Innovations | 17 | 27 | Sustainability and Machine Learning for SDGs | 17_sustainable_goal_sustainability_development | [‘sustainable’, ‘goal’, ‘sustainability’, ‘development’, ‘energy’, ‘analysis’, ‘bibliometric’, ‘waste’, ‘sdgs’, ‘management’, ‘country’, ‘growth’, ‘solid’, ‘latent’, ‘bibliometrics’, ‘approach’, ‘procurement’, ‘socioeconomic’, ‘deionization’, ‘intelligence’, ‘artificial’, ‘wireless’, ‘environmental’, ‘allocation’, ‘dirichlet’, ‘governance’, ‘smart’, ‘text’, ‘removal’, ‘businessmanagement’, ‘ecopsychology’, ‘faradaic’, ‘ecocivilization’, ‘achieving’, ‘sourcing’, ‘hyacinth’, ‘corruption’, ‘cee’, ‘city’, ‘network’, ‘challenge’, ‘water’, ‘data’, ‘safety’, ‘insight’, ‘thing’, ‘sdg’, ‘wastewater’, ‘inclusive’, ‘united’, ‘forest’, ‘renewable’, ‘nation’, ‘mining’, ‘concept’, ‘treatment’, ‘ecological’, ‘evolution’, ‘big’, ‘tourism’, ‘carbon’, ‘view’, ‘perspective’, ‘global’, ‘internet’, ‘status’, ‘corporate’, ‘climate’, ‘trend’, ‘world’, ‘transportation’, ‘education’, ‘transfer’, ‘area’, ‘responsible’, ‘event’, ‘generation’, ‘mapping’, ‘machine’, ‘topic’, ‘clustering’, ‘efficiency’, ‘action’, ‘construction’, ‘state’, ‘vision’, ‘power’, ‘identifying’, ‘vosviewer’, ‘control’, ‘china’, ‘research’, ‘experimentalinductive’, ‘electrode’, ‘electrocoagulation’, ‘holistic’, ‘eichhorniacrassipes’, ‘energystorage’, ‘functionality’, ‘hexacyanoferrate’] | [‘bibliometric’, ‘bibliometrics’, ‘sdgs’, ‘sdg’, ‘sustainability’, ‘topic’, ‘sustainable’, ‘latent’, ‘environmental’, ‘achieving’] | [‘sustainability’, ‘bibliometric’, ‘sdgs’, ‘latent’, ‘socioeconomic’, ‘smart’, ‘ecopsychology’, ‘ecocivilization’, ‘sdg’, ‘wastewater’] | |
Bibliometric and Scientometric Analysis of Ethical and Responsible Research in AI28 | 27 | 15 | Artificial Intelligence for Ethical and Responsible Research | 27_ethic_explainable_ai_responsible | [‘ethic’, ‘explainable’, ‘ai’, ‘responsible’, ‘ethical’, ‘explanation’, ‘computer’, ‘vision’, ‘bibliometric’, ‘intelligence’, ‘artificial’, ‘graph’, ‘explainability’, ‘reproductive’, ‘xai’, ‘mapping’, ‘worldwide’, ‘citnetexplorer’, ‘synthetic’, ‘counterfactual’, ‘analysis’, ‘assisted’, ‘implication’, ‘issue’, ‘challenge’, ‘research’, ‘health’, ‘conference’, ‘legal’, ‘healthcare’, ‘survey’, ‘vosviewer’, ‘virtue’, ‘understandability’, ‘recourse’, ‘interpretability’, ‘ingredient’, ‘lem’, ‘posthoc’, ‘humanlike’, ‘hope’, ‘infertility’, ‘gaydar’, ‘elsi’, ‘secret’, ‘seven’, ‘exergaming’, ‘aisupported’, ‘commercial’, ‘tailoring’, ‘comprehensibility’, ‘surrogacy’, ‘strand’, ‘machinelike’, ‘mitochondrial’, ‘bias’, ‘content’, ‘international’, ‘metric’, ‘fairness’, ‘replacement’, ‘dilemma’, ‘sexual’, ‘bigdata’, ‘inequality’, ‘fair’, ‘case’, ‘data’, ‘burden’, ‘recovery’, ‘black’, ‘trustworthiness’, ‘guide’, ‘consideration’, ‘field’, ‘smote’, ‘proceeding’, ‘geographic’, ‘technology’, ‘oftheart’, ‘box’, ‘better’, ‘africa’, ‘molecular’, ‘digital’, ‘definition’, ‘highquality’, ‘interpretable’, ‘robotics’, ‘key’, ‘therapy’, ‘imaging’, ‘translational’, ‘gap’, ‘dissemination’, ‘publishing’, ‘innovation’, ‘participatory’, ‘system’, ‘past’] | [‘ai’, ‘bibliometric’, ‘aisupported’, ‘survey’, ‘highquality’, ‘research’, ‘interpretable’, ‘interpretability’, ‘explanation’, ‘humanlike’] | [‘ai’, ‘ethical’, ‘xai’, ‘citnetexplorer’, ‘assisted’, ‘interpretability’, ‘surrogacy’, ‘bigdata’, ‘oftheart’, ‘participatory’] | |
Bibliometric and Scientometric Analysis of Emerging Technologies in Cryptocurrency and Blockchain | 28 | 15 | Blockchain and Artificial Intelligence for Research Impact Analysis | 28_blockchain_thing_internet_iot | [‘blockchain’, ‘thing’, ‘internet’, ‘iot’, ‘5g’, ‘cryptocurrency’, ‘system’, ‘mobile’, ‘bitcoin’, ‘computing’, ‘machine’, ‘intrusion’, ‘security’, ‘detection’, ‘cloud’, ‘price’, ‘network’, ‘triangulation’, ‘autonomic’, ‘trusted’, ‘cryptocurrencies’, ‘dispute’, ‘prisma’, ‘challenge’, ‘ict’, ‘anomaly’, ‘resolution’, ‘environment’, ‘alternative’, ‘criterion’, ‘ml’, ‘paradigm’, ‘edge’, ‘dirichlet’, ‘allocation’, ‘bibliometric’, ‘making’, ‘latent’, ‘learning’, ‘future’, ‘direction’, ‘industrial’, ‘scientometric’, ‘analysis’, ‘research’, ‘domain’, ‘data’, ‘application’, ‘control’, ‘use’, ‘id’, ‘resourcemanagement’, ‘checking’, ‘tapr’, ‘prisma2020’, ‘enclave’, ‘confidentiality’, ‘mimo’, ‘contract’, ‘litigation’, ‘cyberphysical’, ‘currency’, ‘malpractice’, ‘ao’, ‘south’, ‘aquila’, ‘line’, ‘supplychain’, ‘hai’, ‘hedge’, ‘haven’, ‘1981’, ‘6g’, ‘unleashing’, ‘adr’, ‘smart’, ‘publication’, ‘intelligence’, ‘visualization’, ‘ai’, ‘embedded’, ‘contemporary’, ‘banking’, ‘volatility’, ‘multi’, ‘prominent’, ‘sdn’, ‘egovernance’, ‘korea’, ‘decision’, ‘analytics’, ‘operational’, ‘bibliometry’, ‘stacked’, ‘safe’, ‘mediation’, ‘bidirectional’, ‘advance’, ‘massive’, ‘agent’] | [‘iot’, ‘ict’, ‘scientometric’, ‘ai’, ‘blockchain’, ‘publication’, ‘bibliometric’, ‘ml’, ‘cyberphysical’, ‘smart’] | [‘blockchain’, ‘5g’, ‘cryptocurrency’, ‘bitcoin’, ‘ict’, ‘latent’, ‘scientometric’, ‘id’, ‘prisma2020’, ‘smart’] | |
Impact of Active Learning and Educational Innovations on Student Engagement and Learning Outcomes | 32 | 12 | Flipped Classroom and Active Learning in Higher Education | 32_flipped_active_student_classroom | [‘flipped’, ‘active’, ‘student’, ‘classroom’, ‘engagement’, ‘learning’, ‘curator’, ‘fashion’, ‘exhibition’, ‘multinational’, ‘metal’, ‘museum’, ‘continuous’, ‘interdisciplinary’, ‘lotkas’, ‘collaboration’, ‘blended’, ‘response’, ‘programming’, ‘implementation’, ‘education’, ‘law’, ‘program’, ‘engineering’, ‘college’, ‘undergraduate’, ‘automated’, ‘experience’, ‘review’, ‘border’, ‘summer’, ‘iated’, ‘cocurricular’, ‘hispanic’, ‘hsi’, ‘heavy’, ‘serving’, ‘confchem’, ‘millenia’, ‘gerontology’, ‘crossdisciplinary’, ‘publishable’, ‘experiential’, ‘extramural’, ‘nursingeducation’, ‘fermentation’, ‘20112015’, ‘asking’, ‘science’, ‘institution’, ‘20002015’, ‘aging’, ‘nigeria’, ‘learned’, ‘printing’, ‘engaging’, ‘guided’, ‘framework’, ‘strategy’, ‘community’, ‘successful’, ‘congress’, ‘hivaids’, ‘higher’, ‘assessment’, ‘tool’, ‘project’, ‘university’, ‘studying’, ‘exposure’, ‘technology’, ‘pathway’, ‘teaching’, ‘paper’, ‘bibliometrics’, ‘second’, ‘integrating’, ‘highquality’, ‘3d’, ‘graduate’, ‘device’, ‘investigation’, ‘competency’, ‘designbased’, ‘cooccurrence’, ‘highereducation’, ‘proposal’, ‘stem’, ‘design’, ‘current’, ‘bibliometric’, ‘common’, ‘research’, ‘biology’, ‘funding’, ‘characteristic’, ‘conference’, ‘subject’, ‘mathematics’, ‘activity’] | [‘bibliometric’, ‘education’, ‘bibliometrics’, ‘teaching’, ‘nursingeducation’, ‘institution’, ‘studying’, ‘learned’, ‘learning’, ‘student’] | [‘flipped’, ‘active’, ‘curator’, ‘collaboration’, ‘education’, ‘iated’, ‘cocurricular’, ‘experiential’, ‘nursingeducation’, ‘nigeria’] | |
Impact and Evaluation of Online Learning through Bibliometric and Scientometric Analysis | 7 | 47 | Machine Learning and Artificial Intelligence in Higher Education | 7_online_education_learning_student | [‘online’, ‘education’, ‘learning’, ‘student’, ‘distance’, ‘higher’, ‘elearning’, ‘open’, ‘covid19’, ‘mooc’, ‘engagement’, ‘moocs’, ‘access’, ‘educational’, ‘course’, ‘performance’, ‘bibliometric’, ‘pandemic’, ‘community’, ‘cognitive’, ‘motivation’, ‘theory’, ‘school’, ‘acceptance’, ‘blended’, ‘belief’, ‘web’, ‘science’, ‘analysis’, ‘trend’, ‘technology’, ‘inquiry’, ‘impact’, ‘collaborative’, ‘medium’, ‘mathematics’, ‘participation’, ‘input’, ‘graduate’, ‘growth’, ‘teacher’, ‘stem’, ‘university’, ‘study’, ‘mode’, ‘social’, ‘research’, ‘success’, ‘model’, ‘epistemological’, ‘microcredentials’, ‘planned’, ‘facetoface’, ‘mindfulness’, ‘fun’, ‘challenge’, ‘informationretrieval’, ‘retention’, ‘affair’, ‘outreach’, ‘instructor’, ‘lecture’, ‘factor’, ‘curriculum’, ‘epistemic’, ‘citnetexplorer’, ‘massive’, ‘selfefficacy’, ‘mind’, ‘gamification’, ‘scopus’, ‘vosviewer’, ‘k12’, ‘presence’, ‘general’, ‘collaboration’, ‘outcome’, ‘mixed’, ‘stress’, ‘evidencebased’, ‘learner’, ‘knn’, ‘perspective’, ‘institution’, ‘facebook’, ‘scholarship’, ‘application’, ‘doctoral’, ‘choice’, ‘medical’, ‘20’, ‘intelligent’, ‘framework’, ‘competition’, ‘video’, ‘publication’, ‘agenda’, ‘change’, ‘critical’, ‘transformation’] | [‘moocs’, ‘mooc’, ‘elearning’, ‘bibliometric’, ‘online’, ‘education’, ‘educational’, ‘scholarship’, ‘institution’, ‘course’] | [‘online’, ‘education’, ‘elearning’, ‘mooc’, ‘engagement’, ‘moocs’, ‘bibliometric’, ‘success’, ‘factor’, ‘gamification’] | |
Impact of Active Learning and Assessment Strategies on Educational Outcomes | 19 | 22 | Academic Curriculum Development and Assessment Using Machine Learning and Artificial Intelligence | 19_active_curriculum_teaching_learning | [‘active’, ‘curriculum’, ‘teaching’, ‘learning’, ‘assessment’, ‘student’, ‘course’, ‘method’, ‘education’, ‘medicine’, ‘biology’, ‘molecular’, ‘strategy’, ‘astronomy’, ‘undergraduate’, ‘casebased’, ‘prehealth’, ‘research’, ‘orientation’, ‘exam’, ‘enzyme’, ‘integration’, ‘formative’, ‘laboratory’, ‘implementation’, ‘simulation’, ‘meme’, ‘disciplinebased’, ‘jenos’, ‘planetarium’, ‘biotechnology’, ‘drama’, ‘multiplechoice’, ‘teachingresearch’, ‘cbl’, ‘metacognitive’, ‘activity’, ‘professional’, ‘development’, ‘catalysis’, ‘evaluation’, ‘behavioral’, ‘postgraduate’, ‘mentoring’, ‘module’, ‘translational’, ‘expression’, ‘exercise’, ‘educational’, ‘pedagogy’, ‘improving’, ‘inquiry’, ‘group’, ‘thinking’, ‘critical’, ‘program’, ‘career’, ‘mobile’, ‘question’, ‘study’, ‘resource’, ‘using’, ‘skill’, ‘work’, ‘teacher’, ‘methodology’, ‘experience’, ‘design’, ‘economics’, ‘introductory’, ‘jena’, ‘juhspecific’, ‘parcel’, ‘outbreak’, ‘interestoriented’, ‘persuasive’, ‘promoting’, ‘workforce’, ‘medicaleducation’, ‘constructive’, ‘compensation’, ‘constructivism’, ‘interactivity’, ‘master’, ‘flexner’, ‘fom’, ‘king’, ‘kom’, ‘fourfactor’, ‘glycobiology’, ‘play’, ‘playing’, ‘lecturer’, ‘mme’, ‘misconception’, ‘lecturetutorials’, ‘socialwork’, ‘broad’, ‘coteaching’, ‘softskill’] | [‘teachingresearch’, ‘curriculum’, ‘education’, ‘pedagogy’, ‘teaching’, ‘medicaleducation’, ‘educational’, ‘prehealth’, ‘learning’, ‘coteaching’] | [‘active’, ‘curriculum’, ‘teaching’, ‘prehealth’, ‘exam’, ‘teachingresearch’, ‘pedagogy’, ‘medicaleducation’, ‘lecturetutorials’, ‘coteaching’] | |
Impact of Online and Digital Learning Innovations on Professional Development and Educational Outcomes22 | 21 | 19 | Online Learning and Health Professional Education | 21_online_health_course_action | [‘online’, ‘health’, ‘course’, ‘action’, ‘learning’, ‘assessment’, ‘education’, ‘care’, ‘virtual’, ‘student’, ‘training’, ‘cancer’, ‘pain’, ‘selfassessment’, ‘professional’, ‘pedagogical’, ‘skill’, ‘nurse’, ‘development’, ‘participatory’, ‘research’, ‘team’, ‘crossboundary’, ‘collaborate’, ‘counselor’, ‘hepatitis’, ‘guinea’, ‘palliative’, ‘discussion’, ‘socioconstructivist’, ‘shortage’, ‘school’, ‘collaboration’, ‘curriculum’, ‘work’, ‘asynchronous’, ‘experience’, ‘worker’, ‘teaching’, ‘distance’, ‘formative’, ‘load’, ‘qualitative’, ‘competency’, ‘blended’, ‘primary’, ‘designbased’, ‘nursing’, ‘openaccess’, ‘medical’, ‘psychology’, ‘creation’, ‘evaluation’, ‘mooc’, ‘higher’, ‘program’, ‘study’, ‘elearning’, ‘practice’, ‘classroom’, ‘disease’, ‘teacher’, ‘design’, ‘tribal’, ‘bl’, ‘encouraging’, ‘culturally’, ‘uganda’, ‘ol’, ‘patientcentred’, ‘pbl’, ‘educationprofessional’, ‘alaska’, ‘aidespractitioners’, ‘counselorsintraining’, ‘app’, ‘technologist’, ‘quasiexperimental’, ‘kenya’, ‘strengthen’, ‘spaced’, ‘share’, ‘provider’, ‘problembased’, ‘inform’, ‘inpatient’, ‘investigative’, ‘implementing’, ‘teachingintensive’, ‘supervisory’, ‘supervision’, ‘indigenous’, ‘struggling’, ‘hp’, ‘3429’, ‘juggling’, ‘counseling’, ‘continuing’, ‘conakry’, ‘communityhealth’] | [‘mooc’, ‘elearning’, ‘online’, ‘virtual’, ‘education’, ‘counselorsintraining’, ‘qualitative’, ‘teaching’, ‘educationprofessional’, ‘evaluation’] | [‘virtual’, ‘participatory’, ‘qualitative’, ‘nursing’, ‘mooc’, ‘elearning’, ‘educationprofessional’, ‘counselorsintraining’, ‘teachingintensive’, ‘communityhealth’] |
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Sources | Publications 1 | Contribution Share (%) | Total Citations 1 | H-Index 1 | Total Citations 2 | H-Index 2 |
---|---|---|---|---|---|---|
Scientometrics | 104 | 6.47 | 1843 | 23 | 57,465 | 144 |
IEEE Access | 53 | 3.3 | 607 | 11 | 916,390 | 242 |
Journal of Informetrics | 31 | 1.93 | 498 | 11 | 17,095 | 90 |
Journal of Scientometric Research | 16 | 1.0 | 37 | 4 | 471 | 8 |
Sustainability | 14 | 0.87 | 126 | 6 | 624,123 | 169 |
Education and Information Technologies | 12 | 0.75 | 124 | 5 | 26,127 | 76 |
Journal of Information Science | 12 | 0.75 | 115 | 5 | 9911 | 77 |
Technological Forecasting and Social Change | 12 | 0.75 | 281 | 8 | 114,767 | 179 |
IEEE Transactions on Engineering Management | 11 | 0.68 | 52 | 4 | 14,772 | 112 |
Frontiers in Psychology | 10 | 0.62 | 43 | 3 | 278,925 | 184 |
Quantitative Science Studies | 10 | 0.62 | 92 | 6 | 3110 | 24 |
Expert Systems with Applications | 8 | 0.5 | 107 | 6 | 273,480 | 271 |
Heliyon | 8 | 0.5 | 34 | 1 | 111,478 | 88 |
Journal of Intelligent & Fuzzy Systems | 8 | 0.5 | 56 | 5 | 50,258 | 82 |
PLoS ONE | 8 | 0.5 | 268 | 4 | 2,920,828 | 435 |
Applied Sciences | 7 | 0.44 | 40 | 3 | - | - |
Information Processing & Management | 7 | 0.44 | 182 | 5 | 38,430 | 123 |
Multimedia Tools and Applications | 7 | 0.44 | 23 | 3 | 109,404 | 106 |
Artificial Intelligence Review | 6 | 0.37 | 139 | 2 | 28,988 | 115 |
Collnet Journal of Scientometrics and Information Management | 6 | 0.37 | 33 | 4 | - | - |
Author | Publication Count 1 | Publication Fractionalized 1 | Productivity Contribution (%) 1 | Global Dataset 2 | |
---|---|---|---|---|---|
Total Citation | H-Index | ||||
Chen, Xieling | 20 | 4.63 | 0.29 | 4391 | 30 |
Xie, Haoran | 19 | 4.38 | 0.27 | 18,770 | 55 |
Zou, Di | 13 | 3.03 | 0.19 | 7332 | 41 |
Hassan, Saeed-Ul | 11 | 2.66 | 0.17 | 4116 | 37 |
Cheng, Gary | 11 | 2.16 | 0.13 | 4792 | 33 |
Aljohani, Naif Radi | 8 | 1.79 | 0.11 | 4825 | 38 |
Afzal, Muhammad Tanvir | 7 | 2.08 | 0.13 | 1825 | 24 |
Mayr, Philipp | 7 | 1.84 | 0.11 | 4198 | 26 |
Bornmann, Lutz | 6 | 2.75 | 0.17 | 31,430 | 88 |
Glanzel, Wolfgang | 6 | 2.33 | 0.15 | 27,548 | 89 |
Wang, Fu Lee | 6 | 1.10 | 0.07 | 5402 | 40 |
Jung, Sukhwan | 5 | 2.17 | 0.14 | 177 | 7 |
Thijs, Bart | 5 | 2.00 | 0.12 | 4259 | 33 |
Thoma, George R. | 5 | 1.83 | 0.11 | - | - |
Safder, Iqra | 5 | 1.17 | 0.07 | 565 | 13 |
Saha, Snehanshu | 5 | 1.09 | 0.07 | 2082 | 21 |
Xia, Feng | 5 | 0.82 | 0.05 | 21,276 | 72 |
Nawaz, Raheel | 5 | 0.75 | 0.05 | 5726 | 39 |
Amjad, Tehmina | 4 | 1.42 | 0.09 | 1445 | 20 |
Ahmed, Sheraz | 4 | 1.03 | 0.06 | 5533 | 36 |
Country | Publications | Share (%) |
---|---|---|
China | 446 | 28.34 |
United States | 240 | 15.25 |
India | 108 | 6.86 |
Germany | 65 | 4.13 |
United Kingdom | 55 | 3.49 |
Spain | 51 | 3.24 |
Australia | 44 | 2.8 |
Canada | 37 | 2.35 |
France | 31 | 1.97 |
South Korea | 31 | 1.97 |
Pakistan | 30 | 1.91 |
Brazil | 27 | 1.72 |
Italy | 26 | 1.65 |
Netherlands | 24 | 1.52 |
Russia | 22 | 1.4 |
Japan | 21 | 1.33 |
Iran | 18 | 1.14 |
Romania | 17 | 1.08 |
Singapore | 17 | 1.08 |
Indonesia | 14 | 0.89 |
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Arsalan, M.H.; Mubin, O.; Al Mahmud, A.; Khan, I.A.; Hassan, A.J. Mapping Data-Driven Research Impact Science: The Role of Machine Learning and Artificial Intelligence. Metrics 2025, 2, 5. https://doi.org/10.3390/metrics2020005
Arsalan MH, Mubin O, Al Mahmud A, Khan IA, Hassan AJ. Mapping Data-Driven Research Impact Science: The Role of Machine Learning and Artificial Intelligence. Metrics. 2025; 2(2):5. https://doi.org/10.3390/metrics2020005
Chicago/Turabian StyleArsalan, Mudassar Hassan, Omar Mubin, Abdullah Al Mahmud, Imran Ahmed Khan, and Ali Jan Hassan. 2025. "Mapping Data-Driven Research Impact Science: The Role of Machine Learning and Artificial Intelligence" Metrics 2, no. 2: 5. https://doi.org/10.3390/metrics2020005
APA StyleArsalan, M. H., Mubin, O., Al Mahmud, A., Khan, I. A., & Hassan, A. J. (2025). Mapping Data-Driven Research Impact Science: The Role of Machine Learning and Artificial Intelligence. Metrics, 2(2), 5. https://doi.org/10.3390/metrics2020005