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Digital trauma-recovery programs now generate unprecedented volumes of survivor-authored data, offering a lens into lived experience that extends beyond traditional, clinician-interpreted studies. This paper analyzes 7,700 “hopes for healing” submitted by survivors engaging with Bloom, a global gender-based-violence recovery platform, to examine what large-scale language data can reveal about unmet needs and trajectories of healing. Drawing on trauma-recovery theory (Herman, 1992; Sinko et al., 2021) and the Transtheoretical Model of Change, we employ a hybrid computational–qualitative approach to map survivor hopes across domains of safety, belonging, worthiness, and meaning-making. Findings show that while most survivors focus on safety and relational trust, smaller clusters centered on dignity, growth, and purpose carry disproportionate policy significance. These micro-signals expose critical design and funding gaps in long-term recovery support. The study also refines and extends the GBV-HEAL ontology, capturing diverse pathways and readiness stages through survivor-authored language. Together, the results demonstrate how ethically interpreted digital data can serve as a new form of policy evidence—a “listening infrastructure” for trauma-aware, equitable, and adaptive healing systems.