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MentalHelp: A Multi-Task Dataset for Mental Health in Social Media

Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSNConference contribution/Paperpeer-review

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MentalHelp: A Multi-Task Dataset for Mental Health in Social Media. / Raihan, Md Nishat; Puspo, Sadiya Sayara Chowdhury ; Farabi, Shafkat et al.
Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024). ed. / Nicoletta Calzolari; Min-Yen Kan; Veronique Haste; Alessandro Lenci; Sakriani Sakti; Nianwen Xue. ELRA and ICCL, 2024. p. 11196-11203.

Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSNConference contribution/Paperpeer-review

Harvard

Raihan, MN, Puspo, SSC, Farabi, S, Bucur, A-M, Ranasinghe, T & Zampieri, M 2024, MentalHelp: A Multi-Task Dataset for Mental Health in Social Media. in N Calzolari, M-Y Kan, V Haste, A Lenci, S Sakti & N Xue (eds), Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024). ELRA and ICCL, pp. 11196-11203, The 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation, Torino, Italy, 20/05/24. <https://aclanthology.org/2024.lrec-main.977>

APA

Raihan, M. N., Puspo, S. S. C., Farabi, S., Bucur, A.-M., Ranasinghe, T., & Zampieri, M. (2024). MentalHelp: A Multi-Task Dataset for Mental Health in Social Media. In N. Calzolari, M.-Y. Kan, V. Haste, A. Lenci, S. Sakti, & N. Xue (Eds.), Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024) (pp. 11196-11203). ELRA and ICCL. https://aclanthology.org/2024.lrec-main.977

Vancouver

Raihan MN, Puspo SSC, Farabi S, Bucur AM, Ranasinghe T, Zampieri M. MentalHelp: A Multi-Task Dataset for Mental Health in Social Media. In Calzolari N, Kan MY, Haste V, Lenci A, Sakti S, Xue N, editors, Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024). ELRA and ICCL. 2024. p. 11196-11203

Author

Raihan, Md Nishat ; Puspo, Sadiya Sayara Chowdhury ; Farabi, Shafkat et al. / MentalHelp : A Multi-Task Dataset for Mental Health in Social Media. Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024). editor / Nicoletta Calzolari ; Min-Yen Kan ; Veronique Haste ; Alessandro Lenci ; Sakriani Sakti ; Nianwen Xue. ELRA and ICCL, 2024. pp. 11196-11203

Bibtex

@inproceedings{7952a8394ada413e86836cc3fbfbada3,
title = "MentalHelp: A Multi-Task Dataset for Mental Health in Social Media",
abstract = "Early detection of mental health disorders is an essential step in treating and preventing mental health conditions. Computational approaches have been applied to users{\textquoteright} social media profiles in an attempt to identify various mental health conditions such as depression, PTSD, schizophrenia, and eating disorders. The interest in this topic has motivated the creation of various depression detection datasets. However, annotating such datasets is expensive and time-consuming, limiting their size and scope. To overcome this limitation, we present MentalHelp, a large-scale semi-supervised mental disorder detection dataset containing 14 million instances. The corpus was collected from Reddit and labeled in a semi-supervised way using an ensemble of three separate models - flan-T5, Disor-BERT, and Mental-BERT.",
author = "Raihan, {Md Nishat} and Puspo, {Sadiya Sayara Chowdhury} and Shafkat Farabi and Ana-Maria Bucur and Tharindu Ranasinghe and Marcos Zampieri",
year = "2024",
month = may,
day = "20",
language = "English",
pages = "11196--11203",
editor = "Nicoletta Calzolari and Min-Yen Kan and Haste, {Veronique } and Alessandro Lenci and Sakriani Sakti and Nianwen Xue",
booktitle = "Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024)",
publisher = "ELRA and ICCL",
note = " The 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation, LREC-COLING 2024 ; Conference date: 20-05-2024 Through 25-05-2024",
url = "https://lrec-coling-2024.org/",

}

RIS

TY - GEN

T1 - MentalHelp

T2 - The 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation

AU - Raihan, Md Nishat

AU - Puspo, Sadiya Sayara Chowdhury

AU - Farabi, Shafkat

AU - Bucur, Ana-Maria

AU - Ranasinghe, Tharindu

AU - Zampieri, Marcos

PY - 2024/5/20

Y1 - 2024/5/20

N2 - Early detection of mental health disorders is an essential step in treating and preventing mental health conditions. Computational approaches have been applied to users’ social media profiles in an attempt to identify various mental health conditions such as depression, PTSD, schizophrenia, and eating disorders. The interest in this topic has motivated the creation of various depression detection datasets. However, annotating such datasets is expensive and time-consuming, limiting their size and scope. To overcome this limitation, we present MentalHelp, a large-scale semi-supervised mental disorder detection dataset containing 14 million instances. The corpus was collected from Reddit and labeled in a semi-supervised way using an ensemble of three separate models - flan-T5, Disor-BERT, and Mental-BERT.

AB - Early detection of mental health disorders is an essential step in treating and preventing mental health conditions. Computational approaches have been applied to users’ social media profiles in an attempt to identify various mental health conditions such as depression, PTSD, schizophrenia, and eating disorders. The interest in this topic has motivated the creation of various depression detection datasets. However, annotating such datasets is expensive and time-consuming, limiting their size and scope. To overcome this limitation, we present MentalHelp, a large-scale semi-supervised mental disorder detection dataset containing 14 million instances. The corpus was collected from Reddit and labeled in a semi-supervised way using an ensemble of three separate models - flan-T5, Disor-BERT, and Mental-BERT.

M3 - Conference contribution/Paper

SP - 11196

EP - 11203

BT - Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024)

A2 - Calzolari, Nicoletta

A2 - Kan, Min-Yen

A2 - Haste, Veronique

A2 - Lenci, Alessandro

A2 - Sakti, Sakriani

A2 - Xue, Nianwen

PB - ELRA and ICCL

Y2 - 20 May 2024 through 25 May 2024

ER -