Text mining Islamic law

Abstract

Digital humanities has a venerable pedigree, stretching back to the middle of the twentieth century, but despite noteworthy pioneering contributions it has not become a mainstream practice in Islamic Studies. This essay applies humanities computing to the study of Islamic law. We analyze a representative corpus of works of Islamic substantive law (furu'al-fiqh) from the beginnings of Islamic legal jurisprudence to the early modern period (2nd/8th-13th/19th c.) using several computational tools and methods: text-reuse network analysis based on plain-text annotations and html tags, clustered frequency-based analysis, word clouds, and topic modeling. Applying machine-guided distant reading to Islamic legal texts over the longue-duree, we study (1) the role of the Qur'an, (2) patterns of normative qualifications (ahkam), and (3) the distribution of topics in our corpus. In certain instances the analysis confirms claims made in the scholarly literature on Islamic law, in other instances it corrects such claims.