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Papers
61,005 resultsShowing papers similar to Top2Vec Topic Modeling to Analyze the Dynamics of Publication Activity Related to Environmental Monitoring Using Unmanned Aerial Vehicles
ClearThe application of machine learning to air pollution research: A bibliometric analysis
Researchers conducted a bibliometric analysis of 2,962 studies on machine learning applied to air pollution research from 1990 to 2021, finding that publications surged after 2017, with most research focused on pollutant characterization, short-term forecasting, detection improvement, and emission control. The analysis reveals that machine learning is becoming a powerful tool for understanding atmospheric chemistry and managing air quality, though global collaboration remains limited.
A Topic Modeling Assessment of Emerging Research Trends in the Environmental Science and Engineering Discipline
This study uses topic modeling to identify emerging research trends in environmental science and engineering, revealing growing attention to pollution, climate change, and water quality. Better understanding of research trajectories can help direct collaboration and funding in the field.
Topic modeling discovers trending topics in global research on the ecosystem impacts of microplastics
Researchers applied computational topic modeling to analyze how global microplastic research on ecosystem impacts has evolved across topics, regions, and time periods. The analysis identified trending research themes including terrestrial microplastics and biological interactions while revealing that marine-focused topics remain dominant, helping map the next frontiers for microplastic ecology research.
Soil Organic Carbon Estimation via Remote Sensing and Machine Learning Techniques: Global Topic Modeling and Research Trend Exploration
Researchers used advanced topic modeling and bibliometric analysis to map global research trends in estimating soil organic carbon using remote sensing and machine learning. They identified key research clusters including satellite imagery analysis, deep learning methods, and regional carbon mapping efforts. The study provides a roadmap for future research priorities in monitoring soil carbon stocks, which is critical for understanding climate change.
Unveiling the research landscape of planetscope data in addressing earth-environmental issues: a bibliometric analysis
This bibliometric analysis examined scientific publications using PlanetScope satellite imagery from 2017 to 2023, analyzing 582 documents to map research trends and application areas. The study found growing use of high-resolution PlanetScope data for land use classification, agriculture, and environmental monitoring, with machine learning increasingly applied to enhance analysis.
Analysis of Popular Social Media Topics Regarding Plastic Pollution
Researchers applied five topic modelling techniques including LDA, HDP, LSI, NMF, and STM to 274,404 plastic pollution-related tweets to identify dominant public discourse themes on social media. The analysis revealed that certain techniques were more effective at capturing topic coherence and prevalence, providing policymakers with tools to understand public opinion and target environmental communication strategies.
Mapping the Rise in Machine Learning in Environmental Chemical Research: A Bibliometric Analysis
Researchers conducted a bibliometric analysis of over 3,100 articles to map how machine learning is being applied in environmental chemistry research, including areas like pollutant monitoring and toxicity prediction. They found an exponential surge in publications from 2015 onward, with deep learning and natural language processing emerging as key growth areas. The study identifies microplastics and PFAS among the environmental topics increasingly being studied with AI-driven approaches.
Making waves: Topic modeling discovers trending topics in global research on the ecosystem impacts of microplastics
This is the methodology file for a topic modeling study that used machine learning to analyze trends in global microplastics research. The study identified emerging research themes in the scientific literature on microplastic impacts on ecosystems.
Coronavirus disease-19 in environmental fields: a bibliometric and visualization mapping analysis
Researchers conducted a bibliometric analysis — a large-scale study of scientific publication trends — to map how the scientific community responded to COVID-19 in environmental research fields. The most common topics included air quality impacts, mental health effects, and economic consequences of the pandemic, with China, the USA, and Italy producing the most publications.
Knowledge Landscapes of the Journal of Marine and Island Cultures: Insights from Topic Modeling
Researchers analysed the research trends and knowledge structure of the Journal of Marine and Island Cultures from 2012 to 2024 using topic modelling on 266 published articles, revealing thematic evolution across marine and island cultural studies.
Topic modeling discovers trending topics in global research on the ecosystem impacts of microplastics
A topic-modeling analysis of global microplastic research literature identified nine dominant research themes and tracked how the field has shifted over time — from aquatic to terrestrial environments, from distribution mapping to fate/transport, and from gross physiological toxicity to cellular and genetic damage. The analysis also found that research is heavily concentrated in a handful of wealthy nations, leaving major gaps in understanding microplastic impacts in the most heavily polluted but under-studied regions of the world.
The supporting role of Artificial Intelligence and Machine/Deep Learning in monitoring the marine environment: a bibliometric analysis
This review examines the supporting role of artificial intelligence and machine learning in monitoring and managing plastic pollution, covering applications in remote sensing, image-based plastic detection, and predictive modeling of plastic fate. The authors identify deep learning for image classification and satellite-based detection as the most rapidly advancing AI applications in plastic pollution science.
The landscape of public procurement research: a bibliometric analysis and topic modelling based on Scopus
Researchers conducted a bibliometric analysis and topic modeling of public procurement research published between 1984 and 2022, examining 640 journal articles by over 1,200 authors. The study maps the structure and dynamics of the public procurement knowledge domain and identifies key research themes and trends over nearly four decades of scholarship.
A Study on Environmental Trends and Sustainability in the Ocean Economy Using Topic Modeling: South Korean News Articles
Researchers used topic modeling of over 50,000 South Korean news articles from 2008-2022 to track evolving environmental concerns in ocean economy sectors, revealing shifts in public and media attention toward marine sustainability and pollution issues over time.
Application of Machine learning techniques in environmental governance: A review
This paper is not relevant to microplastics research — it reviews the application of machine learning methods in environmental governance broadly, covering air and water quality monitoring and land use management.
A Bibliometric Analysis of GPS/GNSS Contributions to GIS
Researchers conducted a bibliometric analysis of nearly 3,000 GPS/GNSS-GIS publications from 1988 to 2025, finding roughly 12% annual growth in publication volume, heavy concentration of output among U.S.-affiliated authors, and a recent surge in AI-driven techniques including machine learning and deep learning.
A Bibliometric Analysis of Ocean Plastic Pollution Research: Trends and Future Directions
Researchers conducted a bibliometric analysis of ocean plastic pollution research using Scopus data from 2000 to 2024, applying VOSviewer to map co-authorship networks, keyword co-occurrences, and thematic clusters to identify influential contributors and emerging research directions. The analysis revealed rapid growth in publication volume and identified microplastics, marine debris, and policy-related themes as dominant research foci.
A comprehensive analysis of evolution and underlying connections of water research themes in the 21st century
Researchers conducted a comprehensive bibliometric analysis of articles published in Water Research over the first 21.5 years of the 21st century to map evolving water research themes and their interconnections. The analysis identified stable core topics such as wastewater treatment and adsorption alongside emerging trends, providing a systematic overview of advances in water science and policy.
A Bibliometric perspective on the evolution of research in sludge management: Opportunities and challenges
A bibliometric analysis traced the evolution of research on a specific topic related to microplastics, mapping publication trends, leading authors, and emerging themes over time. Bibliometric studies help identify where the field is growing and where knowledge gaps remain to be filled.
A Study of marine plastic pollution abatement: A bibliometric analysis on status and development trend
Researchers conducted a bibliometric analysis of marine plastic pollution research using R software, finding that global scientific attention has grown substantially, with microplastics emerging as a central focus spanning both macro- and microscale investigations.
Mapping Metaverse Research: Identifying Future Research Areas Based on Bibliometric and Topic Modeling Techniques
This study uses data analysis techniques to map research trends in the metaverse, an immersive digital environment concept. It analyzed 595 journal articles and found exponential growth in metaverse research since 2020, identifying key themes and active researchers. This paper is not related to microplastics or human health.
A Bibliometric Analysis of Geological Hazards Monitoring Technologies
Researchers conducted a bibliometric analysis of 12,123 geological hazard monitoring publications from 1976 to 2023 using VOSviewer and CiteSpace to identify research trends and hot topics. Current hotspots include deep learning, data fusion, and GNSS-based early warning systems, with this study providing a meta-level roadmap for future geological hazard monitoring research.
Scientometric analysis and scientific trends on microplastics research
Researchers performed a scientometric analysis of microplastics research using 2,872 publications from the Web of Science database spanning 2004 to 2020. The bibliometric analysis mapped contributing countries, institutions, key authors, trending keywords, and future research directions in the field. The study found that microplastics research has grown rapidly, with increasing attention to environmental pollution across various ecosystems.
How do humans recognize and face challenges of microplastic pollution in marine environments? A bibliometric analysis
Researchers performed a bibliometric analysis of 1,898 publications on marine microplastics, mapping research growth, collaboration networks, and thematic trends over time, and predicting that future research will increasingly focus on biological effects, human health impacts, and policy-relevant risk characterization.