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TrailMap: Pheromone-Based Adaptive Peer Matching for Sustainable Online Support Communities
Harold Ngabo-Woods1,2, Larisa Dunai3, Isabel Seguí Verdú3
1Universitat Politècnica de València, 46022 Valencia, Spain.
TrailMap, a novel algorithm inspired by ant colonies, improves online mental health support by efficiently matching users and reducing wait times. This nature-inspired approach enhances community sustainability and equitable participation.
Area of Science:
- Computer Science
- Social Sciences
- Mental Health
Background:
- Online peer support platforms are crucial for mental health but suffer from inefficient user matching and unequal participation.
- Inefficient matching leads to "super-helper" burnout and reduced platform effectiveness.
Purpose of the Study:
- Introduce TrailMap, a novel peer-matching algorithm inspired by ant colony foraging strategies.
- Validate TrailMap's effectiveness in improving efficiency, workload equity, and user experience in online support communities.
Main Methods:
- Agent-based simulation to assess TrailMap's performance against random routing.
- A four-week randomized controlled pilot study with human participants to evaluate real-world effectiveness.
Main Results:
- TrailMap reduced mean time to a helpful response by over 70% in simulations.
- Human trials showed a 76% reduction in median wait time and higher perceived helpfulness.
- Improved workload equity and enhanced socio-technical sustainability of online support communities.
Conclusions:
- TrailMap offers a practical, nature-inspired solution for building more resilient and equitable online mental health support communities.
- The algorithm enhances efficiency and sustainability by balancing workload and identifying effective helpers.
- TrailMap improves access to effective mental health support through optimized peer matching.
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