Hope as Infrastructure: Event-Driven Narrative Analytics to Govern Emotional Cultures in Grand-Challenge Work

Instrument organizations tackling grand challenges (e.g., anti-exploitation NGOs, international organizations) with event logs and narrative data (emails, chat, town halls). Use text mining and affect analysis to track “unexpectedness” in emotion and attention patterns following triggering events. Identify which signals—recognition, prosocial acts, leader framing—restore or erode hope, and run field experiments on narrative interventions. This approach addresses the lack of event-calibrated, real-time measures and intervention tests for hope cultures, borrowing signaling logic to model how certain messages function as stronger hope signals and indirect reciprocity to theorize how public altruism and reputational gains propagate hope across networks. The project builds on critical realist sequences emphasizing co-presence, symbolic sharing, and power dynamics, combining qualitative event ethnography with computational analysis while avoiding anthropomorphizing AI. It moves emotions from a latent backdrop to governable infrastructure, producing measurable “hope recovery” profiles after shocks such as funding cuts or ethical crises. This establishes a new subfield—emotional infrastructure governance—linking narrative analytics to organizational resilience in mission-driven and international settings.

References:

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