Article
Computer Science, Interdisciplinary Applications
Enrico di Bella, Luca Gandullia, Sara Preti
Summary: This paper analyzes the complex structure and characteristics of co-authorship networks among researchers at the Italian Institute of Technology, aiming to identify a possible relationship between researchers' positions in the graphs and their scientific productivity and quality. The study utilizes Social Network Analysis techniques to describe the relational structure of the researchers' group and its evolution over time, examining two different co-authorship networks based on papers published by the institute from 2006 to 2019.
Article
Computer Science, Interdisciplinary Applications
Xiaomei Bai, Fuli Zhang, Jinzhou Li, Zhong Xu, Zeeshan Patoli, Ivan Lee
Summary: This paper explores collaboration and productivity in science careers, quantifies the impact of collaboration in collaboration-citation networks, and proposes the SCIRank model. It also examines the typical duration of research collaborations.
Article
Computer Science, Information Systems
Parul Khurana, Kiran Sharma
Summary: This study examines the emerging trends and collaboration patterns of blockchain technology through bibliometric and network analysis, highlighting the impact of open-access publications, collaboration patterns, ranking, and key areas in the literature.
MULTIMEDIA TOOLS AND APPLICATIONS
(2023)
Article
Medicine, Research & Experimental
Andrei-Flavius Radu, Simona Gabriela Bungau, Paul Andrei Negru, Mihai Florin Marcu, Felicia Liana Andronie-Cioara
Summary: Rheumatoid arthritis is a chronic autoimmune disorder, and pharmacotherapy plays a crucial role in its treatment. This study provides a comprehensive analysis of RA pharmacotherapy in terms of scientific impact, current research status, and trends, which is important for improving disease outcomes.
BIOMEDICINE & PHARMACOTHERAPY
(2022)
Article
Computer Science, Interdisciplinary Applications
Lu Huang, Xiang Chen, Yi Zhang, Yihe Zhu, Suyi Li, Xingxing Ni
Summary: Collaboration is crucial for scientific advancement, but finding suitable research partners has become more challenging due to the increase in academic publications. This paper introduces a method that simulates a dynamic network from static data to improve the quality of collaboration recommendations. A case study in the field of information science validates the reliability of the proposed method and provides practical insights for stakeholders.
Article
Computer Science, Artificial Intelligence
Wenbin Zhao, Jishuang Luo, Tongrang Fan, Yan Ren, Yukun Xia
Summary: As scientific research becomes increasingly complex, collaborative approaches are vital for promoting knowledge and resource sharing. Studying the internal organizational structure and evolution mechanism of scientific research collaboration is crucial for managing research work and formulating policies. This paper focuses on core node evaluation, community detection, and visual layout algorithms for scientific research collaboration networks, aiming to enhance the understanding of the community structure within these networks.
PATTERN RECOGNITION LETTERS
(2021)
Article
Health Care Sciences & Services
Ferran Catala-Lopez, Adolfo Alonso-Arroyo, Matthew J. Page, Lourdes Castello-Cogollos, Brian Hutton, Manuel Ridao, Rafael Tabares-Seisdedos, Rafael Aleixandre-Benavent, David Moher
Summary: This study investigated the scientific collaboration and citation metrics of reporting guidelines for health research. A cross-sectional analysis of published articles and network analyses of collaborations were conducted. The results identified key actors, intense collaborations, and 'citation classics' in the field, which could be used to strengthen collaborations for developing and disseminating reporting guidelines for health research.
JOURNAL OF CLINICAL EPIDEMIOLOGY
(2023)
Article
Clinical Neurology
Zhuo Li, Chi Xu, Jun Fu, Maimaiti Zulipikaer, Tao Deng, Jiying Chen
Summary: Central sensitization is a state of hypersensitivity in the central nervous system that plays a crucial role in chronic pain. The United States leads academic activity in this field, which is steadily growing. Research hotspots include the pathogenesis of central sensitization in neuropathic pain and related clinical trials.
JOURNAL OF PAIN RESEARCH
(2022)
Article
Computer Science, Artificial Intelligence
Bilal H. Butt, Muhammad Rafi, Muhammad Sabih
Summary: The study of scientific networks focuses on exploring social networks in academic research, using nodes such as authors, articles, or journals and connections like citation, co-citation, or co-authorship. By analyzing publicly available citation metadata, various techniques including centrality analysis, community detection, and clustering coefficient are applied to understand the structure and contributions of scientific networks. The use of Python scripts for network analysis aids in comprehending multidimensional scientific scholarship.
PEERJ COMPUTER SCIENCE
(2021)
Article
Computer Science, Artificial Intelligence
Junshuai Song, Xiaoru Qu, Zehong Hu, Zhao Li, Jun Gao, Ji Zhang
Summary: The paper introduces a subgraph-based method named SubGNN for collective fraud detection, which achieves precise fraud detection by learning knowledge reasoning rules on extracted heterogeneous subgraphs. Experimental results demonstrate the clear advantages of this method in fraud detection.
Article
Computer Science, Information Systems
Lianwei Qu, Jing Yang, Yong Wang
Summary: With the prevalence of heterogeneous networks, there is an increasing need for privacy protection mechanisms in homogeneous networks within these networks. Homogeneous networks are vulnerable to malicious attacks when they are published, which is why we propose a privacy protection method based on differential privacy uncertainty for publishing homogeneous networks. Our method involves partitioning the network into community subgraphs and bridging subgraphs, utilizing differential privacy and random perturbations for coding and decoding, perturbing the node degree sequence, designing various reconstruction strategies, and performing postprocessing to fuse the subgraphs. Extensive experimental analysis on real datasets demonstrates the effectiveness of our method in guaranteeing privacy and availability of homogeneous network data publishing.
INFORMATION SCIENCES
(2023)
Article
Computer Science, Interdisciplinary Applications
Nataliya Matveeva, Ivan Sterligov, Andrey Lovakov
Summary: One major characteristic of research is international collaboration, and the post-Soviet countries have experienced significant changes in their collaboration patterns, with decreased collaboration among themselves and increased collaboration with Western countries.
Article
Physics, Multidisciplinary
Xiao Fan Liu, Hou-Jin Chen, Wu-Jiu Sun
Summary: This study examines the phenomenon of adaptive topological coevolution between scientific collaboration and paper citation networks, and proposes a concise model framework. The topological evolution of a network may have a profound influence on others, and adaptation to structural evolutions is a crucial mechanism in the topological evolution of complex networks.
PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS
(2021)
Article
Computer Science, Interdisciplinary Applications
Yunpei Tian, Gang Li, Jin Mao
Summary: Scientific communities are fundamental structures in academic activity and tracking their evolution is crucial for understanding the development of science. In this study, an event-based Group Evolution Prediction task is formulated and interpretable machine learning approaches are applied. Random Forest performs the best in predicting seven defined evolution events, and feature analysis reveals the importance of connectivity, community size, research topic consistency, diversity, average node age, and intermediary nodes. This methodology provides insights into the mechanisms behind scientific community evolution, which can be valuable for scholars and policymakers.
JOURNAL OF INFORMETRICS
(2023)
Article
Biotechnology & Applied Microbiology
Juan Chen, Lizi Pan, Yan Lu, Ting Zhang, Dongzi Xu, Shu Yan, Zhaolian Ouyang
Summary: In recent years, the field of mRNA vaccines has experienced rapid development, leading to significant changes in global scientific collaboration. A bibliometric and social network analysis revealed that domestic inter-institutional cooperation increased significantly, while international cooperation decreased significantly. More countries participated in international collaboration, with the US, the UK and Germany being the top three throughout all periods. Additionally, significant correlations were found between collaboration type and publication impact, as well as between geographical distance and collaborative publication counts.
HUMAN VACCINES & IMMUNOTHERAPEUTICS
(2023)
Article
Computer Science, Interdisciplinary Applications
Hao Teng, Nan Wang, Hongyu Zhao, Yingtong Hu, Haitao Jin
Summary: In this paper, a new method based on functional semantic knowledge (FOP) is proposed for patent similarity calculation. Furthermore, patent STS datasets are processed and released as benchmarks. Preliminary results show that FOP-based methods are more suitable for STS tasks when combined with IPC codes, weights' assignments, and patent pre-trained vectors.
JOURNAL OF INFORMETRICS
(2024)
Article
Computer Science, Interdisciplinary Applications
Cristina Urdiales, Eduardo Guzman
Summary: Subject categorization of scientific publications is important for evaluating paper quality. Traditional mechanisms for categorization have been questioned, and a new method based on association rules is proposed. The method automatically defines publication categories based on the repetition or absence of relevant descriptors. The empirical study in the field of Physical Sciences and Engineering shows that the proposed method produces consistent and suitable categorization results.
JOURNAL OF INFORMETRICS
(2024)
