Mapping the Frontier: A Bibliometric Analysis of Artificial Intelligence Applications in Local and Regional Studies DOI Creative Commons
Camelia Delcea, Ionuț Nica, Ștefan Ionescu

et al.

Algorithms, Journal Year: 2024, Volume and Issue: 17(9), P. 418 - 418

Published: Sept. 20, 2024

This study aims to provide a comprehensive bibliometric analysis covering the common areas between artificial intelligence (AI) applications and research focused on local or regional contexts. The covers period year 2002 2023, utilizing data sourced from Web of Science database. Employing Bibliometrix package within RStudio VOSviewer software, identifies significant increase in AI-related publications, with an annual growth rate 22.67%. Notably, key journals such as Remote Sensing, PLOS ONE, Sustainability rank among top contributing sources. From perspective prominent affiliations, institutions like Duy Tan University, Ton Duc Thang Chinese Academy Sciences emerge leading contributors, Vietnam, Portugal, China being countries highest citation counts. Furthermore, word cloud is able highlight recurring keywords, including “model”, “classification”, “prediction”, “logistic regression”, “innovation”, “performance”, “random forest”, “impact”, “machine learning”, “artificial intelligence”, “deep learning”. co-occurrence network reveals five clusters, amongst them neural network”, “regional development”, “climate change”, economy”, “management”, “technology”, “risk”, “fuzzy inference system”. Our findings support fact that AI increasingly employed address complex challenges, resource management urban planning. applications, machine learning algorithms networks, have become essential for optimizing processes decision-making at level. concludes while holds vast potential transforming research, ongoing international collaboration development adaptable models are maximizing benefits these technologies. Such efforts will ensure effective implementation diverse contexts, thereby supporting sustainable development.

Language: Английский

AI on Wheels: Bibliometric Approach to Mapping of Research on Machine Learning and Deep Learning in Electric Vehicles DOI Open Access
Adrian Domenteanu, Liviu‐Adrian Cotfas,

Paul Diaconu

et al.

Electronics, Journal Year: 2025, Volume and Issue: 14(2), P. 378 - 378

Published: Jan. 19, 2025

The global transition to sustainable energy systems has placed the use of electric vehicles (EVs) among areas that might contribute reducing carbon emissions and optimizing usage. This paper presents a bibliometric analysis interconnected domains EVs, artificial intelligence (AI), machine learning (ML), deep (DL), revealing significant annual growth rate 56.4% in research activity. Key findings include identification influential journals, authors, countries, collaborative networks have driven advancements this domain. study highlights emerging trends, such as integration renewable sources, vehicle-to-grid (V2G) schemes, application AI EV battery optimization, charging infrastructure, consumption prediction. also uncovers challenges addressing information security concerns. By reviewing top-cited papers, underlines transformative potential AI-driven solutions enhancing performance scalability. results can be useful for practitioners, academics, policymakers.

Language: Английский

Citations

3

A Bibliometric Analysis of Text Mining: Exploring the Use of Natural Language Processing in Social Media Research DOI Creative Commons
Andra Sandu, Liviu‐Adrian Cotfas, Aurelia Stănescu

et al.

Applied Sciences, Journal Year: 2024, Volume and Issue: 14(8), P. 3144 - 3144

Published: April 9, 2024

Natural language processing (NLP) plays a pivotal role in modern life by enabling computers to comprehend, analyze, and respond human meaningfully, thereby offering exciting new opportunities. As social media platforms experience surge global usage, the imperative capture better understand messages disseminated within these networks becomes increasingly crucial. Moreover, occurrence of adverse events, such as emergence pandemic or conflicts various parts world, heightens users’ inclinations towards platforms. In this context, paper aims explore scientific literature dedicated utilization NLP research, with goal highlighting trends, keywords, collaborative authorship that contribute proliferation papers field. To achieve objective, we extracted analyzed 1852 from ISI Web Science database. An initial observation reveals remarkable annual growth rate 62.18%, underscoring heightened interest academic community domain. This includes an n-gram analysis review most cited database, comprehensive bibliometric analysis. The insights gained efforts provide essential perspectives identifying pertinent issues addressed through application NLP.

Language: Английский

Citations

11

Guiding Urban Decision-Making: A Study on Recommender Systems in Smart Cities DOI Open Access
Andra Sandu, Liviu‐Adrian Cotfas, Aurelia Stănescu

et al.

Electronics, Journal Year: 2024, Volume and Issue: 13(11), P. 2151 - 2151

Published: May 31, 2024

In recent years, the research community has increasingly embraced topics related to smart cities, recognizing their potential enhance residents’ quality of life and create sustainable, efficient urban environments through integration diverse systems services. Concurrently, recommender have demonstrated continued improvement in accuracy, delivering more precise recommendations for items or content aiding users decision-making processes. This paper explores utilization context cities by analyzing a dataset comprised papers indexed ISI Web Science database. Through bibliometric analysis, key themes, trends, prominent authors institutions, preferred journals, collaboration networks among were extracted. The findings revealed an average annual scientific production growth 25.85%. Additionally, n-gram analysis across keywords, abstracts, titles, keywords plus, along with review selected papers, enriched analysis. insights gained from these efforts offer valuable perspectives, contribute identifying pertinent issues, provide guidance on trends this evolving field. importance lies ability living providing personalized recommendations, optimizing resource utilization, improving processes, ultimately contributing sustainable intelligent environment.

Language: Английский

Citations

10

Beyond Industry 4.0: Tracing the Path to Industry 5.0 through Bibliometric Analysis DOI Open Access
Alexandra-Nicoleta Ciucu Durnoi, Camelia Delcea, Aurelia Stănescu

et al.

Sustainability, Journal Year: 2024, Volume and Issue: 16(12), P. 5251 - 5251

Published: June 20, 2024

The rapid advancement of technology has led to significant milestones in industrial progress, surpassing previous capabilities and presenting new challenges for adaptation. current phase revolutions is characterized by accelerated technological development, particularly automation digitalization. For instance, the global robotics market was valued at approximately USD 43.0 billion 2022 projected reach 70.6 2028. integration human labor alongside robotic machinery, though a tangible reality, may still seem abstract certain regions. Despite recent announcement fourth revolution, Industry 5.0 quickly emerged as standard toward which industries aspire. This study performs bibliometric analysis articles published between 2020 2023 that explores implications these two transition them. Using Clarivate Analytics’ Web Science Core Collection, identifies 154 using Biblioshiny package R, simultaneously discuss 4.0 within their titles, abstracts, or keywords. An impressive annual growth rate 119.47% among papers included dataset underlines interest research community this field. Additionally, key findings include identification prominent sources, prolific authors, highly cited content, well common themes explored across analyzed papers. Among most relevant sources terms number publications, journal Sustainability plays role, holding first position, followed Applied Sciences, Sensors. In motor themes, digital transformation, artificial intelligence, Internet Things, smart manufacturing have been found play role. As result, present contributes understanding evolution from 5.0, highlighting trends, influential research, emerging are shaping future advancements.

Language: Английский

Citations

10

Machine Learning and Deep Learning Applications in Disinformation Detection: A Bibliometric Assessment DOI Open Access
Andra Sandu, Liviu‐Adrian Cotfas, Camelia Delcea

et al.

Electronics, Journal Year: 2024, Volume and Issue: 13(22), P. 4352 - 4352

Published: Nov. 6, 2024

Fake news is one of the biggest challenging issues in today’s technological world and has a huge impact on population’s decision-making way thinking. Disinformation can be classified as subdivision fake news, main purpose which to manipulate generate confusion among people order influence their opinion obtain certain advantages multiple domains (politics, economics, etc.). Propaganda, rumors, conspiracy theories are just few examples common disinformation. Therefore, there an urgent need understand this phenomenon offer scientific community paper that provides comprehensive examination existing literature, lay foundation for future research areas, contribute fight against The present manuscript detailed bibliometric analysis articles oriented towards disinformation detection, involving high-performance machine learning deep algorithms. dataset been collected from popular Web Science database, through use specific keywords such “disinformation”, “machine learning”, or “deep followed by manual check papers included dataset. documents were examined using R tool, Biblioshiny 4.2.0; perspectives various facets: overview, sources, authors, papers, n-gram analysis, mixed analysis. results highlight increased interest topics context learning, supported annual growth rate 96.1%. insights gained bring light surprising details, while study solid basis both area, well development new strategies addressing complex issue ensuring trustworthy safe online environment.

Language: Английский

Citations

5

AI-Driven Smart City Security and Surveillance System: A Bibliometric Analysis DOI
Wei Fan, Syed Ismail Abdul Lathif, Fathey Mohammed

et al.

Studies in computational intelligence, Journal Year: 2025, Volume and Issue: unknown, P. 305 - 328

Published: Jan. 1, 2025

Language: Английский

Citations

0

A systematic analysis of remote sensing and geographic information system applications for flood disaster risk management DOI Creative Commons

Clinton Ekang Amatebelle,

Solomon Temidayo Owolabi, Olumide Abiodun

et al.

Journal of Spatial Science, Journal Year: 2025, Volume and Issue: unknown, P. 1 - 27

Published: March 18, 2025

Language: Английский

Citations

0

The influence of AI on price forecasting. The view of the academic community DOI Creative Commons
Alexandra-Cristina-Daniela Ciuvercă, Simona‐Vasilica Oprea

Journal of Business Economics and Management, Journal Year: 2025, Volume and Issue: 26(1), P. 231 - 254

Published: April 3, 2025

In the context of impressive development Big Data, AI algorithms have proven their efficiency in processing and analyzing large volumes data. Price prediction was no exception. modern economic fields, need for advanced models, with increased efficiency, has become more important. Thus, interest potential solutions terms price all industries also grown progressively. The present study aims to capture, by using several Natural Language Processing techniques, feeling that academic community relation subject way which opinions evolved over years. For this purpose, abstracts works indexed Clarivate WoS addressed topic are included current analysis. scores obtained after analysis reveal a slightly positive attitude towards subject, but nevertheless quite reserved. main topics existing these articles extracted means Latent Dirichlet Allocation. Our makes contributions formulation position specialists scientific evolution. Further, it provides new research directions future studies.

Language: Английский

Citations

0

Emphasizing Grey Systems Contribution to Decision-Making Field Under Uncertainty: A Global Bibliometric Exploration DOI Creative Commons
Andra Sandu,

Paul Diaconu,

Camelia Delcea

et al.

Mathematics, Journal Year: 2025, Volume and Issue: 13(8), P. 1278 - 1278

Published: April 13, 2025

Grey systems are applied in numerous domains, proving a high efficiency predicting and investigating complex systems, where data is insufficient, unknown, or partially known. The have strong contribution the decision-making field under uncertainty, by identifying connection between variables optimizing process of choosing strategies. With time, methods offered grey theory faced continuous adoption various research fields associated with decision-making. In this context, paper aims to provide an in-depth bibliometric exploration, focusing on filtered dataset, gathered from Clarivate Analytics’ Web Science Core Collection database (WoS) for purpose better highlighting uncertainty. Based extracted value registered annual growth rate 17.1%, that scientific community’s focus significant, it has maintained academics’ interest long time. Also, results analysis showed Journal System was most relevant source, while Sifeng Liu provided greatest based number published papers. Nanjing University Aeronautics Astronautics ranked first top affiliation papers, China—the homeland theory—assumes leading contributor country place. review 10 cited papers revealed advantages using

Language: Английский

Citations

0

Navigating the social media market: AI and the challenge of fake news dissemination in the business environment DOI Creative Commons
Monica Ioana Burcă-Voicu, Romana Emilia Cramarenco, Dan‐Cristian Dabija

et al.

Oeconomia Copernicana, Journal Year: 2025, Volume and Issue: 2025(16), P. 79 - 124

Published: March 30, 2025

Research background: Social media plays a crucial role today in enhancing or limiting how fake news is spread. Whether devised by man developed artificial intelligence, it has the power to rapidly change consumers’ minds, encouraging them adopt new behaviors, perceive situations differently, even act total opposition what might be expected. The dynamics of communication highlights need for an organizational response adapted AI technologies and dissemination within social networks. Purpose this article: This paper aims reveal, means bibliometric analysis systematic literature review, generative capabilities intelligence creation spread business environment, acknowledging previous research predicting accurately constant developments contemporary society. Methods: based on PRISMA flowchart examine contribute whilst also highlighting potential regulations standards false information. Initially, database included over 3,400 highly cited articles retrieved from Scopus Web Science, published last years, which 203 were selected inclusion analysis. follows directions related detection methods strategies, legislation policies governing used connected environment. Fake typologies relating advancement are explored. Findings & value added: By analysing important phrases, including information, misinformation, disinformation, mal-information, deepfakes, investigates categorization linked environment concepts. It underscores better truth comprehension significance fact-checking preventing with governance institutional implications terms economics intelligence-generated market. While studies have examined phenomenon several angles, there still gap, as concentrates more consumed rather than created. bridge gap providing comprehensive examination perspectives typology, creation, detection, regulatory means.

Language: Английский

Citations

0