Article
Multidisciplinary Sciences
Concepta McManus, Abilio A. Baeta Neves, Jose Alexandre Diniz Filho, Andrea Q. Maranhao, Antonio G. Souza Filho
Summary: Brazilian science has shown steady improvement in quantity and quality over the past 20 years, but has recently faced financial restrictions since 2015. Increased international collaboration has led to higher citation impact, with diverse research areas showcasing international excellence.
ANAIS DA ACADEMIA BRASILEIRA DE CIENCIAS
(2021)
Article
Multidisciplinary Sciences
Leticia De Oliveira, Fernanda Reichert, Eugenia Zandona, Rossana C. Soletti, Fernanda Staniscuaski
Summary: Despite progress, women are still underrepresented in science worldwide. A recent ranking of influential scientists showed that female scientists are greatly underrepresented, revealing the impact of implicit bias in recognition and promotions in the scientific community. Discussions about the impact of such rankings are crucial to address the gender gap in science.
ANAIS DA ACADEMIA BRASILEIRA DE CIENCIAS
(2021)
Article
Biotechnology & Applied Microbiology
James W. Weis, Joseph M. Jacobson
Summary: This study introduces a machine learning framework called DELPHI to predict long-term impact research papers in the field of biotechnology. The framework provides early warning signals for impactful research by autonomously learning relationships among features in scientific literature. DELPHI has demonstrated the ability to correctly identify key biotechnologies and predict high-impact research papers in the future.
NATURE BIOTECHNOLOGY
(2021)
Article
Computer Science, Interdisciplinary Applications
Samile Andrea de Souza Vanz, Maria Claudia Cabrini Gracio, Sandra Cristina de Oliveira, Zaida Chinchilla-Rodriguez, Domingo Docampo
Summary: Agricultural Sciences in Brazil have become one of the most efficient and sustainable research areas, benefiting from scientific collaboration. This study analyzes the influence of corresponding authorship on the impact of co-authored articles in the Agronomy category. The study finds that articles co-authored by Brazilian authors and international colleagues have a higher citation impact than those with national collaboration, and the influence of corresponding authorship differs between academic and non-academic institutions.
Article
Computer Science, Artificial Intelligence
Yunmei Liu, Min Chen
Summary: Triangular citation, with its formation mechanism lying in the indirect citation between Literature A and Literature C, has been studied in this research by analyzing citation content similarity. It was found that followers C appear more frequently in triangular citations, and factors such as language differences contribute to the high similarity in citation content.
APPLIED SOFT COMPUTING
(2021)
Article
Computer Science, Information Systems
Feiheng Luo, Aixin Sun, Aravind Sesagiri Raamkumar, Mojisola Erdt, Yin-Leng Theng
Summary: Researchers have found that papers receiving citation promoters at an early age experience a rapid growth in citation counts, outperforming other papers in the long term. Additionally, a classification model was developed to predict whether a citing paper would be a citation promoter for its cited paper.
IEEE TRANSACTIONS ON EMERGING TOPICS IN COMPUTING
(2021)
Article
Computer Science, Interdisciplinary Applications
Chaker Jebari, Enrique Herrera-Viedma, Manuel Jesus Cobo
Summary: In recent years, there has been a growing interest in recommending scientific articles based on citation context. This paper presents a comparative analysis of recent studies on context-aware citation recommendation and identifies four gaps in the research, including citation context extraction, classification, temporal and structural aspects, and benchmarking datasets. This study can assist researchers in further exploring these gaps.
Article
Computer Science, Artificial Intelligence
Jinzhu Zhang, Lipeng Zhu
Summary: This paper explores citation recommendation from the perspective of semantic representation of cited papers' relations and content. It designs four forms of citation context and extracts them as the content of cited papers, while also extracting co-citation relationships as cited papers' relations. After calculating the similarity among cited papers, a quantitative evaluation method based on link prediction is designed to identify the most appropriate form of citation content and the optimal method for recommendation.
EXPERT SYSTEMS WITH APPLICATIONS
(2022)
Article
Computer Science, Interdisciplinary Applications
Linhong Xu, Kun Ding, Yuan Lin
Summary: This paper examines the citations of papers in the field of SVM and finds that negative citations do not reduce the impact of the cited papers. Instead, papers with a certain ratio of negative citations tend to have a higher impact. Negative citations also exhibit different characteristics at different stages of SVM development, and they contribute to the improvement of this technology.
Article
Computer Science, Interdisciplinary Applications
Frederique Bordignon
Summary: This study investigates critical citations and finds that their definition lacks consistency. However, they play an important role in knowledge construction and citation analysis. The study proposes three functions for critical citations: criticism, comparison, and questioning, as well as highlighting the lexical and grammatical markers that should be considered in the design of citation polarity detection tools.
Article
Computer Science, Interdisciplinary Applications
Rogerio Mugnaini, Grischa Fraumann, Esteban F. Tuesta, Abel L. Packer
Summary: The study analyzed the use of DOIs in articles by authors from Brazilian institutions, finding higher percentages of DOIs in citations in the hard sciences. International collaboration showed significant differences in citation patterns. Articles with DOIs and mention of research funding had significantly higher percentages, even when considering different areas of knowledge.
Article
Computer Science, Interdisciplinary Applications
Jaewoong Choi, Jiho Lee, Janghyeok Yoon, Sion Jang, Jaeyoung Kim, Sungchul Choi
Summary: This study proposes a dataset called PatentNet to capture the technological citation context of patents, aiming to improve citation recommendation performance. By considering both patent text similarity and technological citation context, the proposed model achieved significant improvements on the benchmark dataset.
Article
Computer Science, Interdisciplinary Applications
Hui Fang
Summary: The current journal indexing methods used to rank journals have been criticized for underestimating the impact of journals with a prolonged influence. This study proposes an integral synchronic journal impact factor (IIF) that combines the features of synchronic and diachronic impact factors. By borrowing the idea of the new CiteScore, the IIF is modified to improve its stability over time. The experimental results show that the modified journal index retains the advantages of the IIF while being more stable.
Article
Computer Science, Information Systems
Yi Bu, Mengyang Li, Weiye Gu, Win-bin Huang
Summary: The paper proposes a new measurement for quantifying journals' diversity by utilizing abstracts of scientific publications in journals, namely topic diversity (TD). This method has the potential to be widely used in scientometrics.
JOURNAL OF THE ASSOCIATION FOR INFORMATION SCIENCE AND TECHNOLOGY
(2021)
Article
Computer Science, Information Systems
Chao Min, Yi Bu, Ding Wu, Ying Ding, Yi Zhang
Summary: This paper introduces a dynamic citation process perspective to identify citation patterns of scientific breakthroughs. Some citation metrics show significant discriminative power and reflect the temporal and structural characteristics of scientific breakthroughs.
INFORMATION PROCESSING & MANAGEMENT
(2021)