Moderator Assistant: A Natural Language Generation-Based Intervention to Support Mental Health via Social Media |
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| Authors: | M Sazzad Hussain Juchen Li Louise A Ellis Laura Ospina-Pinillos Tracey A Davenport Rafael A Calvo |
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| Institution: | 1. School of Electrical and Information Engineering, The University of Sydney, Sydney, NSW, Australia;2. Health and Biosecurity, CSIRO, Epping, Sydney, NSW, Australia;3. Faculty of Medicine, The University of Sydney, Sydney, NSW, Australia |
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| 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. |
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| Keywords: | interventions mental health NLG online support groups social media |
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