Mind the Gap: Predicting, Explaining and Reducing Time-to-First-Comment (Reply Gap) in Online Mental-Health Communities

Guangrui Fan; Dandan Liu; Lihu Pan

AAAI 2026technical0 citations

Mind the Gap: Predicting, Explaining and Reducing Time-to-First-Comment (Reply Gap) in Online Mental-Health Communities

Abstract

Online peer-support communities are vital for mental health, but their therapeutic benefit hinges on receiving a timely and helpful first reply. Posts that languish unanswered can exacerbate feelings of distress and abandonment. This paper develops and validates an integrated framework to predict, explain, and reduce this ``reply gap" on Reddit. First, using survival analysis on over 91,000 posts (2018–2025), we show that a deep learning model (DySurv) can accurately predict reply times (C-Index = 0.742), with a post

BibTeX

@inproceedings{aaai2026_mindthegappredic,
  title = {Mind the Gap: Predicting, Explaining and Reducing Time-to-First-Comment (Reply Gap) in Online Mental-Health Communities},
  author = {Guangrui Fan and Dandan Liu and Lihu Pan},
  booktitle = {AAAI 2026},
  year = {2026}
}