ULLAH Isaac
- Anthropology, San Diego State University, San Diego, United States of America
- Buildings archaeology, Computational archaeology, Environmental archaeology, Geoarchaeology, Landscape archaeology, Mediterranean, Neolithic, Paleoenvironment, Remote sensing, Spatial analysis, Theoretical archaeology
- recommender
Recommendations: 0
Review: 1
Review: 1
Social Network Analysis, Community Detection Algorithms, and Neighbourhood Identification in Pompeii
A Valuable Contribution to Archaeological Network Research: A Case Study of Pompeii
Recommended by David Laguna-Palma based on reviews by Matthew Peeples, Isaac Ullah and Philip VerhagenThe paper entitled 'Social Network Analysis, Community Detection Algorithms, and Neighbourhood Identification in Pompeii' [1] presents a significant contribution to the field of archaeological network research, particularly in the challenging task of identifying urban neighborhoods within the context of Pompeii. This study focuses on the relational dynamics within urban neighborhoods and examines their indistinct boundaries through advanced analytical methods. The methodology employed provides a comprehensive analysis of community detection, including the Louvain and Leiden algorithms, and introduces a novel Convex Hull of Admissible Modularity Partitions (CHAMP) algorithm. The incorporation of a network approach into this domain is both innovative and timely.
The potential impact of this research is substantial, offering new perspectives and analytical tools. This opens new avenues for understanding social structures in ancient urban settings, which can be applied to other archaeological contexts beyond Pompeii. Moreover, the manuscript is not only methodologically solid but also well-written and structured, making complex concepts accessible to a broad audience.
In conclusion, this study represents a valuable contribution to the field of archaeology, particularly for archaeological network research. Their results not only enhance our knowledge of Pompeii but also provide a robust framework for future studies in similar historical contexts. Therefore, this publication advances our understanding of social dynamics in historical urban environments. The rigorous analysis, combined with the innovative application of network algorithms, makes this study a noteworthy addition to the existing body of network science literature. It is recommended for a wide range of scholars interested in the intersection of archaeology, history, and network science.
Reference
[1] Notarian, Matthew. 2024. Social Network Analysis, Community Detection Algorithms, and Neighbourhood Identification in Pompeii. https://doi.org/10.5281/zenodo.8305968