Topic Modeling as a Tool to Identify Research Diversity: A Study across Dental Disciplines DOI Open Access
Maria Teresa Colangelo, Stefano Guizzardi, Carlo Galli

et al.

Metrics, Journal Year: 2024, Volume and Issue: 1(1), P. 3 - 3

Published: Oct. 13, 2024

This study investigates the diversity and evolution of research topics within dental sciences from 1994 to 2023, using Topic modeling Shannon’s entropy as a measure diversity. We analyzed dataset 412,036 scientific articles across six disciplines: Orthodontics, Prosthodontics, Periodontics, Implant Dentistry, Oral Surgery, Restorative Dentistry. relies on BERTopic identify distinct each field. The revealed significant shifts in focus over time, with some disciplines exhibiting robust growth article numbers, such Periodontics Prosthodontics. However, despite overall increase publications, number per discipline varied, Dentistry increasing at faster rate exceeding 50 last 15 years. observed an diversification efforts levels consistently above 2 progressively increasing. In contrast, fields high publication output, maintained more specialized focus, reflected remaining below 1.5. Surgery showed steep until 2000, after which it stabilized. Taken together, our findings describe dynamic nature highlight balance several key areas

Language: Английский

A deep understanding of influencer marketing in the tourism industry: a structural analysis of unstructured text DOI
Hyunsang Son, Young Eun Park

Current Issues in Tourism, Journal Year: 2024, Volume and Issue: unknown, P. 1 - 11

Published: June 26, 2024

Using both a word frequency approach and cutting-edge transfer learning technique for natural language processing with BERTopic, the present study analysed entire texts from top 40 travel influencers' Instagram posts (n = 23,223). Among 256 features that we initially extracted, ranked 19 using machine algorithm XGBoost estimated effects of these on consumer engagement Negative Binomial regression. The results show seasonal trips, destination recommendations, recommendations fashion during trip, emphasising travel-related emotion generate higher level engagement. For message strategy, specifically focusing linguistic features, it is recommended influencers use analytic, authentic, want-related, space-related words in caption but should avoid too many hashtags. Also, overall, sending messages night, are long or emojis.

Language: Английский

Citations

5
Leveraging LLMs for Efficient Topic Reviews DOI Creative Commons
Bady Gana, Andrés Leiva-Araos, Héctor Allende‐Cid

et al.

Applied Sciences, Journal Year: 2024, Volume and Issue: 14(17), P. 7675 - 7675

Published: Aug. 30, 2024

This paper presents the topic review (TR), a novel semi-automatic framework designed to enhance efficiency and accuracy of literature reviews. By leveraging capabilities large language models (LLMs), TR addresses inefficiencies error-proneness traditional methods, especially in rapidly evolving fields. The significantly improves processes by integrating advanced text mining machine learning techniques. Through case study approach, offers step-by-step methodology that begins with query generation refinement, followed semi-automated identify relevant articles. LLMs are then employed extract categorize key themes concepts, facilitating an in-depth analysis. approach demonstrates transformative potential natural processing With average similarity 69.56% between generated indexed keywords, effectively manages growing volume scientific publications, providing researchers robust strategies for complex synthesis advancing knowledge various domains. An expert analysis highlights positive Fleiss’ Kappa score, underscoring significance interpretability results.

Language: Английский

Citations

4
Navigating artificial general intelligence development: societal, technological, ethical, and brain-inspired pathways DOI Creative Commons
Raghu Raman, Robin M. Kowalski, Krishnashree Achuthan

et al.

Scientific Reports, Journal Year: 2025, Volume and Issue: 15(1)

Published: March 11, 2025

This study examines the imperative to align artificial general intelligence (AGI) development with societal, technological, ethical, and brain-inspired pathways ensure its responsible integration into human systems. Using PRISMA framework BERTopic modeling, it identifies five key shaping AGI's trajectory: (1) societal integration, addressing broader impacts, public adoption, policy considerations; (2) technological advancement, exploring real-world applications, implementation challenges, scalability; (3) explainability, enhancing transparency, trust, interpretability in AGI decision-making; (4) cognitive ethical considerations, linking evolving architectures frameworks, accountability, consequences; (5) systems, leveraging neural models improve learning efficiency, adaptability, reasoning capabilities. makes a unique contribution by systematically uncovering underexplored themes, proposing conceptual that connects AI advancements practical multifaceted technical, challenges of development. The findings call for interdisciplinary collaboration bridge critical gaps governance, alignment while strategies equitable access, workforce adaptation, sustainable integration. Additionally, highlights emerging research frontiers, such as AGI-consciousness interfaces collective offering new integrate human-centered applications. By synthesizing insights across disciplines, this provides comprehensive roadmap guiding ways balance innovation responsibilities, advancing progress well-being.

Language: Английский

Citations

0
Leveraging social media for public health: NLP implementations for blood donation data analysis in Japan DOI Creative Commons

Roberto Espinoza,

Kazumasa Kishimoto,

Chang Liu

et al.

Social Network Analysis and Mining, Journal Year: 2025, Volume and Issue: 15(1)

Published: April 3, 2025

Language: Английский

Citations

0
Product Detection in Unmanned Supermarkets Based on Optimized YOLOv8 DOI
Fei Zhao, Liang Gao,

Yang He

et al.

Communications in computer and information science, Journal Year: 2025, Volume and Issue: unknown, P. 233 - 240

Published: Jan. 1, 2025

Language: Английский

Citations

0
Unraveling media perspectives: a comprehensive methodology combining large language models, topic modeling, sentiment analysis, and ontology learning to analyse media bias DOI
Orlando Jähde,

Thorsten Weber,

Rüdiger Buchkremer

et al.

Journal of Computational Social Science, Journal Year: 2025, Volume and Issue: 8(2)

Published: Feb. 25, 2025

Language: Английский

Citations

0
Agenda-setting effects for covid-19 vaccination: Insights from 10 million textual data from social media and news articles using BERTopic DOI
Hyunsang Son, Young Eun Park

International Journal of Information Management, Journal Year: 2025, Volume and Issue: 83, P. 102907 - 102907

Published: April 8, 2025

Language: Английский

Citations

0
Machine Learning for Depression Detection on Web and Social Media DOI Open Access

Lin Gan,

Yingqi Guo, Tao Yang

et al.

International Journal on Semantic Web and Information Systems, Journal Year: 2024, Volume and Issue: 20(1), P. 1 - 28

Published: April 26, 2024

Depression, a significant psychiatric disorder, affects individuals' physical well-being and daily functioning. This focused analysis provides comprehensive exploration of contemporary research conducted between 2012 2023 that delves into the utilization sophisticated machine learning methodologies aimed at identifying correlates depression within social media content. Our study meticulously dissects various data sources performs examination different algorithms cited in researched articles literature, aiming to pinpoint an approach can enhance detection accuracy. Furthermore, we have scrutinized use varied from platforms pinpointed emerging trends, notably spotlighting novel applications artificial neural networks for image processing classification, along with advanced gait models. results offer essential direction future on enhancing precision, acting as valuable reference academic industry scholars this field.

Language: Английский

Citations

1
Topic Modeling as a Tool to identify Research Diversity: A Study Across Dental Disciplines DOI Open Access
Maria Teresa Colangelo, Stefano Guizzardi, Carlo Galli

et al.

Published: Aug. 22, 2024

This study investigates the diversity and evolution of research topics within dental sciences from 1994 to 2023 using topic modeling Shannon's entropy as a measure diversity. We analyzed dataset 412036 scientific articles across six disciplines: Orthodontics, Pros-thodontics, Periodontics, Implant Dentistry, Oral Surgery, Restorative Dentistry. relies on BERTopic identify distinct each field. The revealed significant shifts in focus over time, with some disciplines exhibiting robust growth article numbers such Periodontics Prosthodontics. application an increasing diversification efforts while others, like Prosthodontics, spite their size high number topics, maintain more specialized focus. Taken together, our findings describe dynamic nature re-search highlight balance several key areas

Language: Английский

Citations

1
Topic Modeling as a Tool to Identify Research Diversity: A Study across Dental Disciplines DOI Open Access
Maria Teresa Colangelo, Stefano Guizzardi, Carlo Galli

et al.

Metrics, Journal Year: 2024, Volume and Issue: 1(1), P. 3 - 3

Published: Oct. 13, 2024

This study investigates the diversity and evolution of research topics within dental sciences from 1994 to 2023, using Topic modeling Shannon’s entropy as a measure diversity. We analyzed dataset 412,036 scientific articles across six disciplines: Orthodontics, Prosthodontics, Periodontics, Implant Dentistry, Oral Surgery, Restorative Dentistry. relies on BERTopic identify distinct each field. The revealed significant shifts in focus over time, with some disciplines exhibiting robust growth article numbers, such Periodontics Prosthodontics. However, despite overall increase publications, number per discipline varied, Dentistry increasing at faster rate exceeding 50 last 15 years. observed an diversification efforts levels consistently above 2 progressively increasing. In contrast, fields high publication output, maintained more specialized focus, reflected remaining below 1.5. Surgery showed steep until 2000, after which it stabilized. Taken together, our findings describe dynamic nature highlight balance several key areas

Language: Английский

Citations

0