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    <abstract>Mental burnout refers to a psychological syndrome induced by chronic stress that negatively impacts the emotional and physical well-being of individuals. From the occupational context to personal hobbies, burnout is pervasive across domains and therefore affects the morale and productivity of society as a whole. Currently, no linguistic resources are available for the analysis or detection of burnout language. We address this gap by introducing a dataset annotated for burnout language. Given that social media is a platform for sharing life experiences and mental health struggles, our work examines the manifestation of burnout language in Reddit posts. We introduce a contextual word sense disambiguation approach to identify the specific meaning or context in which the word “burnout” is used, distinguishing between its application in mental health (e.g., job-related stress leading to burnout) and non-mental health contexts (e.g., engine burnout in a mechanical context). We create a dataset of 2,330 manually labeled Reddit posts for this task, as well as annotating the reason the poster associates with their burnout (e.g., professional, personal, non-traditional). We train machine learning models on this dataset achieving a minimum F1 score of 0.84 on the different tasks. We make our dataset of annotated Reddit post IDs publicly available to help advance future research in this field.</abstract>
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%0 Conference Proceedings
%T Inferring Mental Burnout Discourse Across Reddit Communities
%A Sabri, Nazanin
%A Pham, Anh C.
%A Kakkar, Ishita
%A ElSherief, Mai
%Y Dementieva, Daryna
%Y Ignat, Oana
%Y Jin, Zhijing
%Y Mihalcea, Rada
%Y Piatti, Giorgio
%Y Tetreault, Joel
%Y Wilson, Steven
%Y Zhao, Jieyu
%S Proceedings of the Third Workshop on NLP for Positive Impact
%D 2024
%8 November
%I Association for Computational Linguistics
%C Miami, Florida, USA
%F sabri-etal-2024-inferring
%X Mental burnout refers to a psychological syndrome induced by chronic stress that negatively impacts the emotional and physical well-being of individuals. From the occupational context to personal hobbies, burnout is pervasive across domains and therefore affects the morale and productivity of society as a whole. Currently, no linguistic resources are available for the analysis or detection of burnout language. We address this gap by introducing a dataset annotated for burnout language. Given that social media is a platform for sharing life experiences and mental health struggles, our work examines the manifestation of burnout language in Reddit posts. We introduce a contextual word sense disambiguation approach to identify the specific meaning or context in which the word “burnout” is used, distinguishing between its application in mental health (e.g., job-related stress leading to burnout) and non-mental health contexts (e.g., engine burnout in a mechanical context). We create a dataset of 2,330 manually labeled Reddit posts for this task, as well as annotating the reason the poster associates with their burnout (e.g., professional, personal, non-traditional). We train machine learning models on this dataset achieving a minimum F1 score of 0.84 on the different tasks. We make our dataset of annotated Reddit post IDs publicly available to help advance future research in this field.
%U https://aclanthology.org/2024.nlp4pi-1.21
%P 224-231

Markdown (Informal)

[Inferring Mental Burnout Discourse Across Reddit Communities](https://aclanthology.org/2024.nlp4pi-1.21) (Sabri et al., NLP4PI 2024)

• Inferring Mental Burnout Discourse Across Reddit Communities (Sabri et al., NLP4PI 2024)

ACL

• Nazanin Sabri, Anh C. Pham, Ishita Kakkar, and Mai ElSherief. 2024. Inferring Mental Burnout Discourse Across Reddit Communities. In Proceedings of the Third Workshop on NLP for Positive Impact, pages 224–231, Miami, Florida, USA. Association for Computational Linguistics.