Islam and Data Science Roundup

  • In “Analysis of mystical concepts in Khaghani’s Divan” (Digital Scholarship in the Humanities 35, no. 2 (2020)), Ming-Ming Yin, Mohammad Reza Mahmoudi, and Ali Abbasalizadeh apply text mining and machine learning techniques to literary studies by analyzing the work of Afzal Aldin Khahgani E Shervani. After a brief literature review, the authors consider variegated issues such as samples, data collection, and applied approaches. They conclude with the results of the text mining approaches and machine learning techniques as well as their implications.
  • Aqil Azmi, Abdulaziz Al-Qabbany, and Amir Hussain survey all major works that have addressed the subject of hadith through various computational and NLP methods in the article “Computational and natural language processing based studies of hadith literature: A survey” (Artificial Intelligence Review 52, no. 1 (2019)). They group them under three categories: hadith content-based studies, narration-based studies, and overall studies. They conclude by outlining potential research directions in Arabic hadith literature, including novel application of emerging natural language concept based sentiment and emotion mining techniques.
  • German company, Bigitec, creates an application that simulates an interactive hajj experience for those who are unable to attend this year due to COVID-19.

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