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@article{197770,
        author = {Monu Kumar and Annu Yadav},
        title = {Mathematical Modeling of Social Networks for Optimizing Disaster Response Strategies},
        journal = {International Journal of Innovative Research in Technology},
        year = {2026},
        volume = {12},
        number = {11},
        pages = {7832-7836},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=197770},
        abstract = {We present an extended, publication-ready mathematical framework for optimizing disaster response using social network analysis. The framework is purely analytical, relying on graph theory, spectral methods, and probabilistic modeling to (i) identify critical nodes and pathways, (ii) derive closed-form approximations for expected reachability, and (iii) provide provable approximation guarantees for prioritization under budget and equity constraints. The manuscript includes formal propositions, sensitivity analyses, prescriptive guidelines for low-resource deployment, and a comprehensive bibliography for reviewers and practitioners.
“Disasters—arising from natural events or human activities—require timely and well-coordinated response mechanisms to reduce both human impact and material damage. This study develops a mathematical framework that integrates graph-theoretic principles with probabilistic modeling techniques to analyze disaster response dynamics.},
        keywords = {Graph Theory, Social Networks, Disaster Response, Mathematical Modeling, Human Welfare.},
        month = {April},
        }