TrailMap: Pheromone-based adaptive peer matching for sustainable online support communities

Abstract

Online peer support platforms are vital, scalable resources for mental health, yet their effectiveness is frequently undermined by inefficient user matching, severe participation inequality, and subsequent “super-helper” burnout. This study introduces TrailMap, a novel peer-matching algorithm inspired by the decentralised foraging strategies of ant colonies. By treating user interactions as paths that gain or lose “pheromone” based on helpfulness ratings, the system enables the community to collectively and adaptively identify its most effective helpers. A two-phase validation study was conducted. First, an agent-based simulation demonstrated that TrailMap reduced the mean time to a helpful response by over 70% and improved workload equity compared to random routing. Second, a four-week randomised controlled pilot study with human participants confirmed these gains, showing a 76% reduction in median wait time and significantly higher perceived helpfulness ratings. The findings suggest that by balancing the workload, TrailMap enhances not only the efficiency but also the socio-technical sustainability of online support communities. TrailMap provides a practical, nature-inspired method for building more resilient and equitable online support communities, enhancing access to effective mental health support.