Early insights into the Arabic Citation Index

Abstract

The Arabic Citation Index (ARCI) was launched in 2020. This study gives an overview of the scientific literature available in this new database. I analyse ARCI by using metadata available in scientific publications to characterize its coverage. First, I describe the data and the methods used in the analyses. As of October 2020, ARCI indexed 65,208 records covering the 2015-2019 period. Second, I explore the literature distributions at various levels (research domains, countries, languages, open access). Close to 99% of documents indexed are articles. Results reveal the concentration of publications in the Arts & Humanities and Social Sciences fields. Most journals indexed in ARCI are currently published from Egypt, Algeria, Iraq, Jordan and Saudi Arabia. Around 7% of publications in ARCI are published in languages other than Arabic. Then, I use an unsupervised machine learning model, LDA (Latent Dirichlet Allocation) and the text mining algorithms of VOSviewer to uncover the main topics in ARCI. These methods are particularly useful to better understand the topical structure of ARCI. Finally, I suggest few research opportunities after discussing the results of this study.