"Who can help me?": Knowledge Infused Matching of Support Seekers and Support Providers during COVID-19 on Reddit

TL;DR

This paper introduces a knowledge-infused system for efficiently matching COVID-19 support seekers and providers on Reddit, aiming to improve timely care through expert-validated automated matching based on natural language inference.

Contribution

It presents a novel medical knowledge-infused matching approach for COVID-19 support on Reddit, reducing reliance on manual moderation and validated by domain experts.

Findings

Knowledge infusion improves matching accuracy

System effectively classifies support types

Expert validation confirms system efficacy

Abstract

During the ongoing COVID-19 crisis, subreddits on Reddit, such as r/Coronavirus saw a rapid growth in user's requests for help (support seekers - SSs) including individuals with varying professions and experiences with diverse perspectives on care (support providers - SPs). Currently, knowledgeable human moderators match an SS with a user with relevant experience, i.e, an SP on these subreddits. This unscalable process defers timely care. We present a medical knowledge-infused approach to efficient matching of SS and SPs validated by experts for the users affected by anxiety and depression, in the context of with COVID-19. After matching, each SP to an SS labeled as either supportive, informative, or similar (sharing experiences) using the principles of natural language inference. Evaluation by 21 domain experts indicates the efficacy of incorporated knowledge and shows the efficacy the matching system.