Abstract
People on social media share their thoughts and experiences using diseases and symptoms words other than to mention their health, which can introduce biases in data-driven public health applications. For the advancement of HMC research, in this study, we present a Reddit health mention dataset (RHMD), a new dataset of multi-domain Reddit data for the HMC. RHMD is composed of 10015 manually annotated Reddit posts that include 15 common disease or symptom terms and are labeled with four labels: personal health mentions (HMs), nonpersonal HMs, figurative HMs, and hyperbolic HMs. Empirical evaluation using recently proposed methods demonstrates the challenge of labeling user-generated text across these four types. Contributions to this work include the public release of a robustly annotated Reddit dataset (RHMD) for HM tasks and a comprehensive performance analysis of baseline methods. We expect the release of the dataset, and the evaluations will help facilitate the development of new methods for detecting HMs in the user-generated text. The dataset is available at https://github.com/usmaann/RHMD-Health-Mention-Dataset.
| Original language | English |
|---|---|
| Pages (from-to) | 2325-2334 |
| Number of pages | 10 |
| Journal | IEEE Transactions on Computational Social Systems |
| Volume | 10 |
| Issue number | 5 |
| Early online date | 11 Jul 2022 |
| DOIs | |
| Publication status | Published - Oct 2023 |
| Externally published | Yes |
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