RedHOT: A Corpus of Annotated Medical Questions, Experiences, and Claims on Social Media

• URL: http://arxiv.org/abs/2210.06331v1
• Date: Wed, 12 Oct 2022 15:50:32 GMT
• Title: RedHOT: A Corpus of Annotated Medical Questions, Experiences, and Claims on Social Media
• Authors: Somin Wadhwa, Vivek Khetan, Silvio Amir, Byron Wallace
• Abstract summary: We present Reddit Health Online Talk (RedHOT), a corpus of 22,000 richly annotated social media posts from Reddit spanning 24 health conditions. We mark snippets that describe patient Populations, Interventions, and Outcomes (PIO elements) within these claims. We propose a new method to automatically derive (noisy) supervision for this task which we use to train a dense retrieval model.
• Score: 1.5293427903448022
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: We present Reddit Health Online Talk (RedHOT), a corpus of 22,000 richly annotated social media posts from Reddit spanning 24 health conditions. Annotations include demarcations of spans corresponding to medical claims, personal experiences, and questions. We collect additional granular annotations on identified claims. Specifically, we mark snippets that describe patient Populations, Interventions, and Outcomes (PIO elements) within these. Using this corpus, we introduce the task of retrieving trustworthy evidence relevant to a given claim made on social media. We propose a new method to automatically derive (noisy) supervision for this task which we use to train a dense retrieval model; this outperforms baseline models. Manual evaluation of retrieval results performed by medical doctors indicate that while our system performance is promising, there is considerable room for improvement. Collected annotations (and scripts to assemble the dataset), are available at https://github.com/sominw/redhot.

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