Moderator Assistant

a Natural Language Generation-based intervention to support mental health via social media

M. Sazzad Hussain*, Juchen Li, Louise A. Ellis, Laura Ospina-Pinillos, Tracey A. Davenport, Rafael A. Calvo, Ian B. Hickie

*Corresponding author for this work

Research output: Contribution to journalArticle

5 Citations (Scopus)

Abstract

As online mental health support groups become increasingly popular, they require more support from volunteers and trained moderators who help their users through “interventions” (i.e., responding to questions and providing support). We present a system that supports such human interventions using Natural Language Generation (NLG) techniques. The system generates draft responses aimed at reducing moderators’ workload, and improving their efficacy. NLG and human interventions were compared through the ratings of 35 psychology interns. The NLG-based system was capable of generating messages that are grammatically correct with clear language. The system needs improvement, however, moderators can already use it as draft responses.

Original languageEnglish
Pages (from-to)304-329
Number of pages26
JournalJournal of Technology in Human Services
Volume33
Issue number4
DOIs
Publication statusPublished - 2 Oct 2015
Externally publishedYes

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