A Comparison between Two Main Academic Literature Collections: Web of Science and Scopus Databases
By Arezoo Aghaei Chadegani, Hadi Salehi, Melor Md. Yunus, H. Farhadi, Masood Fooladi, Maryam Farhadi, Nader Ale Ebrahim. arXiv.org, 2013
1,751 citations recorded by the source corpus.
Nowadays, the world’s scientific community has been publishing an enormous number of papers in different scientific fields. In such environment, it is essential to know which databases are equally efficient and objective for literature searches. It seems that two most extensive databases are Web of Science and Scopus. Besides searching the literature, these two databases used to rank journals in terms of their productivity and the total citations received to indicate the journals impact, prestige or influence. This article attempts to provide a comprehensive comparison of these databases to answer frequent questions which researchers ask, such as: How Web of Science and Scopus are different? In which aspects these two databases are similar? Or, if the researchers are forced to choose one of them, which one should they prefer? For answering these questions, these two databases will be compared based on their qualitative and quantitative characteristics.
Subfields: Information Systems, Information Systems and Management, Statistics and Probability
View Paper: https://www.semanticscholar.org/paper/2689296a82d8aabcd477c21c2980b41d0cd04881
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In Information Systems
- Ali H. Al-Hoorie
- Maria Spante
- Sylvana Sofkova Hashemi
- Anne Algers
- D. Feliciano
- Mona Lundin
- Lubna Rashid
- Raminta Pranckute
In Information Systems and Management
In Statistics and Probability
Citations in the corpus
- Entrepreneurship Education and Sustainable Development Goals: A literature Review and a Closer Look at Fragile States and Technology-Enabled Approaches (2019, methodology): “generally higher impact compared to SCOPUS [48].”
- Artificial intelligence for waste management in smart cities: a review (2023, background): “To choose the best location for solid waste management system components, another model was developed by researchers that take into account uncertain waste generation rates, facility running costs, transportation costs, and revenue (Chadegani et al. 2013).”
- The Causal Effect of Corporate Governance on Corporate Social Responsibility (2011, neutral): “…classificam os periódicos em termos de sua produtividade e o total de citações recebidas para indicar o impacto, prestígio ou influência dos periódicos, além de disporem de ferramentas necessárias para o refinamento das buscas nas plataformas (Chadegani, et al., 2013; Quartiero & Silva, 2016).”
- What we know and do not know about organizational resilience (2018, background): “coverage than Web of Science, though it does not cover some journals (Chadegani et al., 2013).”
- The seven sins of L2 research: A review of 30 journals’ statistical quality and their CiteScore, SJR, SNIP, JCR Impact Factors (2019, background): “Intense competition exists between these two indexing services, resulting in continuous improvement of their metrics (see Chadegani et al., 2013; Guz & Rushchitsky, 2009).”
- A review on the contribution of crop diversification to Sustainable Development Goal 1 “No poverty” in different world regions (2019, background): “The Web of Science was used because of its broad coverage of studies across disciplines, large temporal records, and collection of scientific studies published in renowned journals (Arezoo et al., 2013).”
- Web of Science (WoS) and Scopus: The Titans of Bibliographic Information in Today's Academic World (2021, background): “However, as both WoS and Scopus are commercial and subscription based products, the worldwide recognition and use of these DBs has resulted in their high price, which makes it rarely affordable for an institution to subscribe to both of them [14].”
- Global Research on Carbon Emissions: A Scientometric Review (2019, methodology): “Also, this scientific method has been adopted in several ways for capturing research knowledge such as bibliometric techniques [43,44,60]; content analysis [39]; literature review [41,68,69]; latent semantic analysis (LSA) [40,51]; and scientometric visualization with different software [45,70].”