Article
Environmental Sciences
Jacopo A. Baggio
Summary: Knowledge production is a co-evolutionary process involving debates, discussions, and assessments among scientists. The evolution of research topics related to climate change shows a shift in focus from emissions and modeling to social impacts, indicating the increasing complexity of climate change literature and the need for new tools like machine learning and natural language processing algorithms to make sense of the evolving body of work.
Article
Business
Omid Faraji, Kaveh Asiaei, Zabihollah Rezaee, Nick Bontis, Ehsan Dolatzarei
Summary: This bibliometric study analyzes the intellectual capital (IC) research from 1975 to 2020 using co-word analysis and social network analysis based on the Web of Science database. The study identifies the most frequent keywords, top-producing country, prolific journal, frequently cited journal, and prolific research institute in IC research. The findings also reveal the variations in frequently used keywords across different geographical regions. This study provides a comprehensive understanding of the current state of IC research, highlights research gaps, and offers suggestions for future studies.
JOURNAL OF INNOVATION & KNOWLEDGE
(2022)
Article
Computer Science, Information Systems
Weifeng Li, Hsinchun Chen
Summary: This study proposes a novel framework for detecting emerging topics in streams of hacker-generated content. The framework outperforms baseline methods in terms of effectiveness and efficiency and demonstrates its practical utility in a hacker forum with important implications for victim companies and law enforcement.
Article
Environmental Sciences
Meihui Li, Yi Lu, Mengjiao Huang
Summary: Negative emissions technologies (NETs), particularly bioenergy with carbon capture and storage (BECCS), are expected to play a significant role in mitigating climate change. However, concerns have been raised regarding the deployment of BECCS. This study used science mapping and visualization analyses to study the evolutionary patterns of BECCS research systematically.
SCIENCE OF THE TOTAL ENVIRONMENT
(2021)
Article
Business
Yang Bai, Hongxiu Li
Summary: This study examines the development of research themes and trends in the field of e-commerce based on prior literature. The findings suggest that research themes have evolved along with the development and diffusion of technology, with some persisting and others emerging in recent years.
ELECTRONIC COMMERCE RESEARCH AND APPLICATIONS
(2022)
Article
Green & Sustainable Science & Technology
Lu Wei, Na Liu, Junhua Chen, Jihong Sun
Summary: This study examines the changes in Chinese COVID-19 policy topics during different stages of the pandemic based on textual policies. The findings indicate that strict epidemic prevention and control is the most important policy topic across all stages. The success of Wuhan City's fight against COVID-19 reflects China's governance characteristics of concentrating power. Practical suggestions for improving Chinese COVID-19 policies are also discussed.
Article
Multidisciplinary Sciences
Francisco Galuppo Azevedo, Fabricio Murai
Summary: Scientific knowledge is a highly connected network and understanding the relationship between research areas is crucial for resource allocation. Two recent works propose methods for creating research maps from scientists' publication records, yet these methods have not been compared in literature.
Article
Computer Science, Interdisciplinary Applications
Xiaoguang Wang, Jing He, Han Huang, Hongyu Wang
Summary: In this study, a new method called MatrixSim based on matrix similarity was proposed to detect the evolution paths of research topics. Compared to traditional methods, MatrixSim considers the local community structure and the similarity of research topics in both nodes and edges. Experimental results confirm that MatrixSim performs well in detecting the evolution paths of research topics.
JOURNAL OF INFORMETRICS
(2022)
Article
Computer Science, Artificial Intelligence
Ke Li, Hubert Naacke, Bernd Amann
Summary: This article introduces a data model and query language for visualizing and exploring topic evolution networks in scientific document archives. The model is independent of specific topic extraction and alignment methods, and proposes a set of metrics for characterizing and filtering meaningful topic evolution patterns. These metrics are particularly useful for visualizing and exploring large topic evolution graphs. An implementation of the model on Apache Spark is presented, along with experimental results for four real-world document archives.
Article
Computer Science, Interdisciplinary Applications
Yating Li, Ye Chen, Qiyu Wang
Summary: This study conducted a dynamic topic analysis of articles on information literacy studies published from 2005 to 2019, identifying nine global topics with varying characteristics and discussing the evolution mechanisms of global and local topics. The study highlighted the importance of multidisciplinary integration in driving future research development.
Article
Computer Science, Interdisciplinary Applications
Lu Huang, Xiang Chen, Yi Zhang, Changtian Wang, Xiaoli Cao, Jiarun Liu
Summary: This study proposes a framework for identifying topic evolutionary pathways based on network analytics, which can extract semantic relationships from the context of titles and abstracts and scientifically reflect the evolution process of topics.
Article
Computer Science, Interdisciplinary Applications
Aliakbar Pourhatami, Mohammad Kaviyani-Charati, Bahareh Kargar, Hamed Baziyad, Maryam Kargar, Carlos Olmeda-Gomez
Summary: Over the past two decades, coronaviruses have significantly impacted human life in terms of health and economy. Researchers have employed co-word analysis to map the intellectual structure of coronavirus literature and identify key themes such as Antibody-Virus Interactions, Emerging Infectious Diseases, and Coronavirus Detection Methods. While considerable research has been conducted, there are still interesting and promising gaps in understanding and exploring areas like Antibody-Virus Interactions and Emerging Infectious Diseases.
Article
Computer Science, Interdisciplinary Applications
Oliver Wieczorek, Said Unger, Jan Riebling, Lukas Erhard, Christian Koss, Raphael Heiberger
Summary: The study reveals a trend of natural science topics rising and humanities topics declining in the field of psychology, particularly more pronounced in leading outlets. Meanwhile, a rise in neurosciences and related methodologies is seen, while traditional approaches such as psychoanalysis are losing popularity.
Article
Information Science & Library Science
Bai Yun, Zhao Yue, Zhou Yaolin
Summary: This study identified the prominent topics, distribution, and association characteristics of Documentary Heritage Preservation and Conservation (DHPAC) research in China through co-word analysis and social network analysis. The research topics in China were unbalanced but distinct, with core topics having less influence on the overall network. Research in this field had formed four continuous evolutionary paths with topics fusion and differentiation coexisting. New hot topics of DHPAC research kept appearing in China.
Article
Chemistry, Multidisciplinary
Tu-Kuang Ho, Wei-Yuan Shih, Wen-Yang Kao, Chin-Hsien Hsu, Cheng-Ying Wu
Summary: This study examines the abstracts of index journals in China and Taiwan and uses text mining and natural language processing (NLP) to analyze the data. The results reveal the scope and trends of sports research in the two regions, emphasizing the need for balanced development and expansion in the field of sports.
APPLIED SCIENCES-BASEL
(2022)
