The Algorithmic Activist: Harnessing AI-Driven Social Network Analysis for Targeted Community Service Interventions
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This study explores the potential of artificial intelligence (AI) and social network analysis (SNA) as synergistic tools in designing more effective and targeted community service interventions. By utilizing algorithmic insights from AI-driven models, particularly those capable of detecting influence patterns, relational dynamics, and community clusters, this research proposes a strategic framework for identifying marginalized groups, mapping social capital, and optimizing resource allocation. The methodology involves the integration of machine learning with network-based metrics such as centrality, modularity, and sentiment propagation to uncover social influencers and information bottlenecks within digital communities. The findings highlight how algorithmic activism—when ethically deployed—can support NGOs, local governments, and grassroots movements in delivering precision-driven programs, minimizing redundancy, and amplifying impact. The study also discusses ethical considerations, including algorithmic bias and data privacy, emphasizing the need for transparent and inclusive AI governance in civic technology initiatives. This research contributes to the emerging discourse on civic AI and its transformative role in public service innovation.
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