Al-Ahadeeth: A Visualization Tool of the Hadiths' Chain of Narrators

Hamada R. H. Al-Absi, Devi G. Kurup, Amina Daoud, Jens Schneider, Wajdi Zaghouani, Saeed Mohd H. M. Al Marri, Younss Ait Mou

Abstract: Hadiths are the records of words, actions, and silent approval attributed to the Prophet Mohammed (PBUH). Their significance is second only to the Holy Quran within the Islamic faith. They have been collected, curated, and published by the most respected Islamic scholars through time. Each Hadith begins with a chain of narrators (sanad), distinguishing them from the main text (Matan), serving as a means for Islamic scholars to assess their strength and veracity. Most people read the approved six books of Hadiths, often focusing solely on the content (Matan) or browsing through topics, neglecting the profound intricacies hidden within the individual narrators’ backgrounds. Furthermore, the data is accessed without a visual user interface, imposing limitations due to the purely text-based nature. To alleviate this, we present Al-Ahadeeth, a visualization tool of the chain of narrators of Hadiths. Mapping narrators and narrated-to relations to nodes and edges in a directed graph, we use node size and edge thickness to show occurrence frequencies. Using the concept of generations, we place nodes on concentric rings based on the topological index to compute a 2D layout. Due to the high degree of interconnection in the community of narrators, traditional graph embedding techniques such as multi-dimensional scaling (MDS), t-distributed stochastic neighbor embedding (t-SNE) or uniform manifold approximation and projection (UMAP) tend to map the entire graph to a single cluster and give unsatisfactory results. In contrast, our approach uses the concept of generations to compute the layout of the graph which places nodes on concentric rings to indicate the generation.