The Arabic Citation Index: Toward a better understanding of Arab scientific literature

Abstract

Abstract The Arabic Citation Index (ARCI) was launched in 2020. This article provides an overview of the scientific literature contained in this new database and explores its possible usage in research evaluation. As of May 2022, ARCI had indexed 138,283 scientific publications published between 2015 and 2020. ARCI’s coverage is characterized by using the metadata available in scientific publications. First, I investigate the distributions of the indexed literature at various levels (research domains, countries, languages, open access). Articles make up nearly all the documents indexed with a share of 99% of ARCI. The Arts & Humanities and Social Sciences fields have the highest concentration of publications. Most indexed journals are published in Egypt, Algeria, Iraq, Jordan, and Saudi Arabia. About 8% of publications in ARCI are published in languages other than Arabic. Second, I use an unsupervised machine learning model, Latent Dirichlet Allocation, and the text mining algorithm of VOSviewer to uncover the main topics in ARCI. These methods provide a better understanding of ARCI’s thematic structure. Next, I discuss how ARCI can complement global standards in the context of a more inclusive research evaluation. Finally, I suggest a few research opportunities after discussing the findings of this study.

Cite this work

No public copy is stored for this record, so only the metadata is cited.

Stored only when both papers are in the corpus — 6 citations exist upstream.

Papers that cite the same references — the relational fallback while embeddings are still backfilling.