36.3923, Confs: 11th Social Media Mining for Health Applications and Health Real-World Data Workshop and Shared Tasks (Online)

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LINGUIST List: Vol-36-3923. Mon Dec 22 2025. ISSN: 1069 - 4875.

Subject: 36.3923, Confs: 11th Social Media Mining for Health Applications and Health Real-World Data Workshop and Shared Tasks (Online)

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Date: 19-Dec-2025
From: Guillermo Lopez Garcia [Guillermo.LopezGarcia at cshs.org]
Subject: 11th Social Media Mining for Health Applications and Health Real-World Data Workshop and Shared Tasks


11th Social Media Mining for Health Applications and Health Real-World
Data Workshop and Shared Tasks
Short Title: #SMM4H-HeaRD 2026

Date: 02-Jul-2026 - 03-Jul-2026
Location: Online
Contact: Guillermo Lopez Garcia
Contact Email: Guillermo.LopezGarcia at cshs.org
Meeting URL: https://healthlanguageprocessing.org/smm4h-2026/

Linguistic Field(s): Computational Linguistics

Submission Deadline: 24-Apr-2026

Social Media Mining for Health Applications and Health Real-World Data
(#SMM4H-HeaRD) 2026 Workshop and Shared Tasks
Workshop:
The Social Media Mining for Health Applications and Health Real-World
Data (#SMM4H-HeaRD) Workshop provides an interdisciplinary forum for
presenting and discussing advances in natural language processing
(NLP), machine learning, and artificial intelligence at the
intersection of health and web-based data. Now in its 11th edition,
the #SMM4H-HeaRD 2026 Workshop will be held online and co-located with
the 64th Annual Meeting of the Association for Computational
Linguistics (ACL 2026).
This year’s edition will emphasize privacy-preserving data sharing and
real-world evaluation, particularly in the context of health-related
text from sources such as social media, electronic health records, and
biomedical literature. In alignment with the ACL 2026 Theme Track on
the “Explainability of NLP Models”, we also invite work that improves
the transparency, interpretability, and trustworthiness of models
applied in high-stakes clinical and public health contexts. Please see
the website for additional information:
https://healthlanguageprocessing.org/smm4h-2026/
Important Dates:
- Submission deadline: April 24, 2026
- Notification of acceptance: May 15, 2026
- Camera-ready papers due: May 25, 2026
- Workshop: July 2-3, 2026
Shared Tasks:
The Social Media Mining for Health Applications and Health Real-World
Data (#SMM4H-HeaRD) shared tasks address natural language processing,
machine learning, and artificial intelligence challenges involved in
analyzing and modeling health-related content from social media and
other real-world data sources. For each of the 8 tasks below, teams
will be provided with annotated training and validation data to
develop their systems, followed by 5 days during which they will run
their systems on unlabeled test data and upload their predictions to
CodaLab. Additional details about the tasks and system description
papers can be found on the website. Please use this form to register:
https://forms.gle/oE9gfaNxFw2f6gyX6
- Task 1: Detection of Adverse Drug Events in Multilingual and
Multi-platform Social Media Posts
- Task 2: Detection of Insomnia in Clinical Notes
- Task 3: Estimating Flu Vaccine Effectiveness from Social Media Posts
- Task 4: Generation of Realistic Medical Dialogue-Note Pairs
- Task 5: Detection of Patient Metadata in SARSCoV-2 Sequencing
Articles
- Task 6: Predicting TNM Staging from TCGA Pathology Reports
- Task 7: Extraction of Social and Clinical Impacts of Substance Use
from Social Media Posts
- Task 8: Multilingual Clinical Entity Annotation Projection and
Extraction
Important Dates:
- Training and validation data available: January 11, 2026
- System predictions for validation data due: April 4, 2026
- Test data available: April 10, 2026
- System predictions for test data due: April 14, 2026
- Submission deadline for system description papers: April 24, 2026
- Notification of acceptance: May 15, 2026
- Camera-ready papers due: May 25, 2026
- Workshop: July 2-3, 2026
Organizing Committee:
- Graciela Gonzalez-Hernandez, Cedars-Sinai Medical Center, USA
- Guillermo Lopez-Garcia, Cedars-Sinai Medical Center, USA
- Dongfang Xu, Cedars-Sinai Medical Center, USA
- Ivan Flores, Cedars-Sinai Medical Center, USA
- Jose Miguel Acitores, Cedars-Sinai Medical Center, USA
- Jacob Berkowitz, Cedars-Sinai Medical Center, USA
- Nicholas Tatonetti, Cedars-Sinai Medical Center, USA
- Ari Z. Klein, University of Pennsylvania, USA
- Abeed Sarker, Emory University, USA
- Sumon Kanti Dey, Emory University, USA
- Ahmad Rezaie Mianroodi, Dalhousie University, Vector Institute,
Canada
- Frank Rudzicz, Dalhousie University, Vector Institute, Canada
- Lisa Raithel, Technische Universität Berlin, Germany
- Roland Roller, DFKI, Germany
- Philippe Thomas, DFKI, Germany
- Yu Zhai, Hong Kong Polytechnic University, Hong Kong
- Tomohiro Nishiyama, Nara Institute of Science and Technology, Japan
- Pierre Zweigenbaum, LISN, CNRS, Université Paris-Saclay, France
- Elena Tutbalina, AIRI, Kazan Federal University, Russia
- Salvador Lima-López, Barcelona Supercomputing Center, Spain
- Judith Rosell, Barcelona Supercomputing Center, Spain
- Martin Krallinger, Barcelona Supercomputing Center, Spain



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