RedditESS: A Mental Health Social Support Interaction Dataset -- Understanding Effective Social Support to Refine AI-Driven Support Tools

Zeyad Alghamdi, Tharindu Kumarage, Garima Agrawal, Mansooreh Karami, Ibrahim Almuteb +1 more
3/27/2025
cs.CLcs.AI

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Abstract

Effective mental health support is crucial for alleviating psychological distress. While large language model (LLM)-based assistants have shown promise in mental health interventions, existing research often defines "effective" support primarily in terms of empathetic acknowledgments, overlooking other essential dimensions such as informational guidance, community validation, and tangible coping strategies. To address this limitation and better understand what constitutes effective support, we introduce RedditESS, a novel real-world dataset derived from Reddit posts, including supportive comments and original posters' follow-up responses. Grounded in established social science theories, we develop an ensemble labeling mechanism to annotate supportive comments as effective or not and perform qualitative assessments to ensure the reliability of the annotations. Additionally, we demonstrate the practical utility of RedditESS by using it to guide LLM alignment toward generating more context-sensitive and genuinely helpful supportive responses. By broadening the understanding of effective support, our study paves the way for advanced AI-driven mental health interventions.

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Cite this paper

@article{alghamdi2025redditess,
  title  = {RedditESS: A Mental Health Social Support Interaction Dataset -- Understanding Effective Social Support to Refine AI-Driven Support Tools},
  author = {Zeyad Alghamdi and Tharindu Kumarage and Garima Agrawal and Mansooreh Karami and Ibrahim Almuteb and Huan Liu},
  year   = {2025},
  eprint = {2503.21888},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2503.21888v1}
}

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