MentSum: A Resource for Exploring Summarization of Mental Health Online Posts
15573Authors
nan
Abstract
AbstractMental health remains a significant challenge of public health worldwide. With increasing popularity of online platforms, many use the platforms to share their mental health conditions, express their feelings, and seek help from the community and counselors. Some of these platforms, such as Reachout, are dedicated forums where the users register to seek help. Others such as Reddit provide subreddits where the users publicly but anonymously post their mental health distress. Although posts are of varying length, it is beneficial to provide a short, but informative summary for fast processing by the counselors. To facilitate research in summarization of mental health online posts, we introduce Mental Health Summarization dataset, MentSum, containing over 24k carefully selected user posts from Reddit, along with their short user-written summary (called TLDR) in English from 43 mental health subreddits. This domain-specific dataset could be of interest not only for generating short summaries on Reddit, but also for generating summaries of posts on the dedicated mental health forums such as Reachout. We further evaluate both extractive and abstractive state-of-the-art summarization baselines in terms of Rouge scores, and finally conduct an in-depth human evaluation study of both user-written and system-generated summaries, highlighting challenges in this research.
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Proceedings of the 13th Conference on Language Resources and Evaluation (LREC 2022), pages 2682–2692 Marseille, 20-25 June 2022 © European Language Resources Association (ELRA), licensed under CC-BY-NC-4.0 2682 MentSum: A Resource for Exploring Summarization of Mental Health Online Posts Sajad Sotudeh1,2*, Nazli Goharian1,2*, Zachary Young2 1Information Retrieval Lab, Georgetown University 2Department of Computer Science, Georgetown University {sajad, nazli}@ir.cs.georgetown.edu, zjy2@georgetown.edu Abstract Mental health remains a significant challenge of public health worldwide. With increasing popularity of online platforms, many use the platforms to share their mental health conditions, express their feelings, and seek help from the community and counselors. Some of these platforms, such as Reachout, are dedicated forums where the users register to seek help. Others such as Reddit provide subreddits where the users publicly but anonymously post their mental health distress. Although posts are of varying length, it is beneficial to provide a short, but informative summary for fast processing by the counselors. To facilitate research in summarization of mental health online posts, we introduce Mental Health Summarization dataset, MENTSUM, containing over 24k carefully selected user posts from Reddit, along with their short user-written summary (called TLDR) in English from 43 mental health subreddits. This domain-specific dataset could be of interest not only for generating short summaries on Reddit, but also for generating summaries of posts on the dedicated mental health forums such as Reachout. We further evaluate both extractive and abstractive state-of-the-art summarization baselines in terms of ROUGE scores, and finally conduct an in-depth human evaluation study of both user-written and system-generated summaries, highlighting challenges in this research. Keywords: Text Summarization, Summarization Dataset, Mental Health Summarization 1. Introduction Mental health has been a global public health challenge for many years and even more so since the COVID- 19 pandemic (Holmes et al., 2020; Pfefferbaum and North, 2020; Otu et al., 2020). Social media has served as a viable platform for many to share their frustrations, emotions, depressions, and also their already diagnosed mental disorders. Figure 1 depicts the growing popu- larity (measured by the number of subscribers) of dis- cussion forums dedicated to three mental disorders in Reddit social discussion website over the years. 1. Online social platforms such as Reddit 2 and Rea- chout 3 have become increasingly popular over the re- cent years due to the vital networking facets that they offer to the community users. These platforms provide users with an opportunity to share different types of user-curated and user-generated content, ranging from daily updates/statuses to sharing personal anecdotes and mental conditions. Users can also interact with other users, carry on conversations through which they can express their feelings and views regarding a spe- cific topic. Platforms such as Reachout are not pub- lic, requiring users to register; users’ content are not visible to anyone but to the permitted users and coun- selors. On the other hand, in the public platforms such as Reddit, users can openly exchange information with each other through community-based subreddits, each of which specified with a certain theme or condi- *Equal …
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AbstractMental health remains a significant challenge of public health worldwide. With increasing popularity of online platforms, many use the platforms to share their mental health conditions, express their feelings, and seek help from the community and counselors. Some of these platforms, such as Reachout, are dedicated forums where the users register to seek help. Others such as Reddit provide subreddits where the users publicly but anonymously post their mental health distress. Although posts are of varying length, it is beneficial to provide a short, but informative summary for fast processing by the counselors. To facilitate research in summarization of mental health online posts, we introduce Mental Health Summarization dataset, MentSum, containing over 24k carefully selected user posts from Reddit, along with their short user-written summary (called TLDR) in English from 43 mental health subreddits. This domain-specific dataset could be of interest not only for generating short summaries on Reddit, but also for generating summaries of posts on the dedicated mental health forums such as Reachout. We further evaluate both extractive and abstractive state-of-the-art summarization baselines in terms of Rouge scores, and finally conduct an in-depth human evaluation study of both user-written and system-generated summaries, highlighting challenges in this research.
Publication Details
- Paper ID:
- 15573
- Year:
- 2022
- Publication:
- TIPSTER
- Publication Type:
- conf
- DOI:
- nan