  The Arabic Citation Index (ARCI) was launched in 2020. This study gives an
overview of the scientific literature available in this new database. By using
metadata available in scientific publications, I analyse ARCI to characterize
the scientific literature published in Arabic. 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.
