The data source of this study is Web of Science Core Collection? Not enough

Liu, Weishu

doi:10.1007/s11192-019-03238-1

Cited by 129 publications

(80 citation statements)

References 19 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…The web-based Web of Science was launched in 1997 and renamed Web of Science Core Collection around 2014 1 . The WoS integrated SCIE, SSCI and A&HCI indexes initially in 1997 2 and expanded its coverage gradually (Liu 2019;Rousseau et al 2018). To keep consistent, this study uses "Web of Science" and the abovementioned three index names as the keywords to retrieve WoS-related records 3 .…”

Section: Methodsmentioning

confidence: 99%

“…By focusing on the database itself, Li et al (2018) conduct a pioneer empirical analysis on the use of Web of Science during 1997 and 2017 and uncover the characteristics of the academic use of WoS across countries/regions, institutions, and knowledge domains. Moreover, in order to depict the non-transparent use of WoS, Liu (2019) also finds that an increasing number of papers have mentioned WoS in their topic field.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

A tale of two databases: the use of Web of Science and Scopus in academic papers

2020

Self Cite

View full text Add to dashboard Cite

Web of Science and Scopus are two world-leading and competing citation databases. By using the Science Citation Index Expanded and Social Sciences Citation Index, this paper conducts a comparative, dynamic, and empirical study focusing on the use of Web of Science (WoS) and Scopus in academic papers published during 2004 and 2018. This brief communication reveals that although both Web of Science and Scopus are increasingly used in academic papers, Scopus as a new-comer is really challenging the dominating role of WoS. Researchers from more and more countries/regions and knowledge domains are involved in the use of these two databases. Even though the main producers of related papers are developed economies, some developing economies such as China, Brazil and Iran also act important roles but with different patterns in the use of these two databases. Both two databases are widely used in meta-analysis related studies especially for researchers in China. Health/medical science related domains and the traditional Information Science & Library Science field stand out in the use of citation databases.

show abstract

Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

A tale of two databases: the use of Web of Science and Scopus in academic papers

2020

Self Cite

View full text Add to dashboard Cite

show abstract

“…The WoS was published in 1997 and renamed the WoS Core Collection around 2014 [ 20 , 21 ]. In this study, we extracted data from Science Citation Index Expanded (SCIE) and Social Sciences Citation Index (SSCI) from initial publication year to 1 May 2020 in the WoS core collection.…”

Section: Data Source and Methodologymentioning

confidence: 99%

The Prediction of Infectious Diseases: A Bibliometric Analysis

Yang

Zhang

2020

IJERPH

View full text Add to dashboard Cite

Objective: The outbreak of infectious diseases has a negative influence on public health and the economy. The prediction of infectious diseases can effectively control large-scale outbreaks and reduce transmission of epidemics in rapid response to serious public health events. Therefore, experts and scholars are increasingly concerned with the prediction of infectious diseases. However, a knowledge mapping analysis of literature regarding the prediction of infectious diseases using rigorous bibliometric tools, which are supposed to offer further knowledge structure and distribution, has been conducted infrequently. Therefore, we implement a bibliometric analysis about the prediction of infectious diseases to objectively analyze the current status and research hotspots, in order to provide a reference for related researchers. Methods: We viewed “infectious disease*” and “prediction” or “forecasting” as search theme in the core collection of Web of Science from inception to 1 May 2020. We used two effective bibliometric tools, i.e., CiteSpace (Drexel University, Philadelphia, PA, USA) and VOSviewer (Leiden University, Leiden, The Netherlands) to objectively analyze the data of the prediction of infectious disease domain based on related publications, which can be downloaded from the core collection of Web of Science. Then, the leading publications of the prediction of infectious diseases were identified to detect the historical progress based on collaboration analysis, co-citation analysis, and co-occurrence analysis. Results: 1880 documents that met the inclusion criteria were extracted from Web of Science in this study. The number of documents exhibited a growing trend, which can be expressed an increasing number of experts and scholars paying attention to the field year by year. These publications were published in 427 different journals with 11 different document types, and the most frequently studied types were articles 1618 (83%). In addition, as the most productive country, the United States has provided a lot of scientific research achievements in the field of infectious diseases. Conclusion: Our study provides a systematic and objective view of the field, which can be useful for readers to evaluate the characteristics of publications involving the prediction of infectious diseases and for policymakers to take timely scientific responses.

show abstract

“…The scientific papers were obtained from the Core Collection of Web of Science (WoS), one of the most relevant bibliographic databases widely used in academia 30 , 31 . Core collection consists of ten sub-datasets (eight citation indexes and two chemical indexes), with information from over 18,000 high impact journals, over 180,000 conference proceedings, and over 80,000 books 32 . Four co-authorship networks were built with the records of specific queries by topic and title, and limiting the document just to scientific articles.…”

Section: Methodsmentioning

confidence: 99%

Analysis of dynamic networks based on the Ising model for the case of study of co-authorship of scientific articles

Hurtado-Marín

Agudelo-Giraldo

Robledo

2021

Sci Rep

View full text Add to dashboard Cite

Two computational methods based on the Ising model were implemented for studying temporal dynamic in co-authorship networks: an interpretative for real networks and another for simulation via Monte Carlo. The objective of simulation networks is to evaluate if the Ising model describes in similar way the dynamic of the network and of the magnetic system, so that it can be found a generalized explanation to the behaviours observed in real networks. The scientific papers used for building the real networks were acquired from WoS core collection. The variables for each record took into account bibliographic references. The search equation for each network considered specific topics trying to obtain an advanced temporal evolution in terms of the addition of new nodes; that means 3 steps, a time to reach the interest of the scientific community, a gradual increase until reaching a peak and finally, a decreasing trend by losing of novelty. It is possible to conclude that both methods are consistent with each other, showing that the Ising model can predict behaviours such as the number and size of communities (or domains) according to the temporal distribution of new nodes.

show abstract

The data source of this study is Web of Science Core Collection? Not enough

Cited by 129 publications

References 19 publications

A tale of two databases: the use of Web of Science and Scopus in academic papers

A tale of two databases: the use of Web of Science and Scopus in academic papers

The Prediction of Infectious Diseases: A Bibliometric Analysis

Analysis of dynamic networks based on the Ising model for the case of study of co-authorship of scientific articles

Contact Info

Product

Resources

About