Use of Bibliometrics Data to Understand the Citation Advantages of Different Open Access Categories in Covid‐19 Related Studies

Autor: Matthew Marsteller, Xiaoju Chen, Neelam Bharti
Jazyk: angličtina
Rok vydání: 2021
Předmět:
Zdroj: Proceedings of the Association for Information Science and Technology. Association for Information Science and Technology
ISSN: 2373-9231
Popis: The number of Open Access (OA) research articles is trending upward. This research aims to understand the correlations between different OA types and the impact of OA research articles evaluated based on the citation numbers. To avoid bias caused by the publication year, we chose to use COVID-19 studies in different fields to take advantage of this topic's quick turnaround of data. We analyzed the bibliometrics data and citation numbers (excluding self-citations) of around 42,000 English language articles published in 2020 related to COVID-19. We evaluated different types of OA categories such as Gold, Bronze, and Hybrid articles separately. Results show that amongst all OA categories, Hybrid/Green and Bronze/Green OA articles had significant citation advantages. Green OA articles returned more citations than articles with the other OA status. Gold OA articles have no citation advantages compared to non-OA articles. Gold/Green OA articles had the highest self-citation rates, followed by Non-OA articles. The results of the study can be used in understanding different OA categories and the reasons for OA choices. Certain strategies can be made accordingly to improve the awareness of OA in different fields and help OA publishers to improve the OA services.
Databáze: OpenAIRE