Quantum-Social Network Analysis for Community Detection: A Comprehensive Review

The dynamics and underlying structure of complex social networks (SNs) can be discovered using community detection. Considering how quantum computing might improve community detection techniques is becoming more and more popular in light of recent developments in computing technology. In this article, the rapidly developing topic of quantum-SN analysis for community discovery is thoroughly reviewed. Community detection is studied in the context of several quantum-inspired techniques, including quantum annealing and quantum-inspired optimization. To make use of the strengths of both conventional SN research methods and quantum computing techniques, hybrid quantum-classical approaches are being investigated. Case studies and applications that have made use of quantum-SN analysis methodologies are reviewed to highlight the practical consequences and potential advantages over conventional methods. The article also highlights the challenges and limitations of using quantum computing for SN analysis, including technical constraints and ethical issues. Finally, prospects and future research objectives in the area of quantum-SN analysis are highlighted. This covers possible developments in quantum algorithms for community detection, the incorporation of quantum computing with other SN research tasks, and the significance of multidisciplinary collaborations.