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#SMM4H 2022 : 7th Social Media Mining for Health Applications - Workshop & Shared Task at COLING 2022


When Oct 16, 2022 - Oct 17, 2022
Where Gyeongju, Republic of Korea
Submission Deadline Aug 20, 2022
Notification Due Sep 1, 2022
Final Version Due Sep 12, 2022
Categories    NLP   text mining   social media   health

Call For Papers

Due to multiple requests, we are extending the deadline to August 20, 2022

Last call for papers, submission deadline is August 20, 2022
Last call for shared task participation, evaluation period starts July 11, 2022
*Apologies if you received multiple copies of this CFP*

Location: Gyeongju, Republic of Korea
Workshop Date: October 16-17, 2022
Important links:
Workshop and Shared task:
Submission link:

The workshop will include two components — a standard workshop and a shared task

The Social Media Mining for Health Applications (#SMM4H) workshop serves as a venue for bringing together researchers interested in automatic methods for the collection, extraction, representation, analysis, and validation of social media data (e.g., Twitter, Reddit, Facebook) for health informatics. The 7th #SMM4H Workshop, co-located at COLING 2022 (, invites 4-page paper (unlimited references in standard COLING format) submissions on original, unpublished research in all aspects at the intersection of social media mining and health. Topics of interest include, but are not limited to:

Methods for the automatic detection and extraction of health-related concept mentions in social media

Mapping of health-related mentions in social media to standardized vocabularies

Deriving health-related trends from social media

Information retrieval methods for obtaining relevant social media data

Geographic or demographic data inference from social media discourse

Virus spread monitoring using social media

Mining health-related discussions in social media

Drug abuse and alcoholism incidence monitoring through social media

Disease incidence studies using social media

Sentinel event detection using social media

Semantic methods in social media analysis

Classifying health-related messages in social media

Automatic analysis of social media messages for disease surveillance and patient education

Methods for validation of social media-derived hypotheses and datasets

Shared task
The workshop organizers this year are hosting 10 shared tasks i.e. NLP challenges as part of the workshop. Participating teams will be provided with a set of annotated posts for developing systems, followed by a three-day window during which they will run their systems on unlabeled test data and upload it to Codalab for evaluation. For additional details about the tasks and information about registration, data access, paper submissions, and presentations, go to

Task 1 – Classification, detection, and normalization of Adverse Events (AE) mentions in tweets (in English)

Task 2 – Classification of stance and premise in tweets about health mandates related to COVID-19 (in English)

Task 3 – Classification of changes in medication treatments in tweets and WebMD reviews (in English)

Task 4 – Classification of tweets self-reporting exact age (in English)

Task 5 – Classification of tweets containing self-reported COVID-19 symptoms (in Spanish)

Task 6 – Classification of tweets which indicate self-reported COVID-19 vaccination status (in English)

Task 7 – Classification of self-reported intimate partner violence on Twitter (in English)

Task 8 – Classification of self-reported chronic stress on Twitter (in English)

Task 9 – Classification of Reddit posts self-reporting exact age (in English)

Task 10 – Detection of disease mentions in tweets – SocialDisNER (in Spanish)

Organizing Committee
Graciela Gonzalez-Hernandez, Cedars-Sinai Medical Center, USA
Davy Weissenbacher, Cedars-Sinai Medical Center, USA
Arjun Magge, University of Pennsylvania, USA
Ari Z. Klein, University of Pennsylvania, USA
Ivan Flores, Cedars-Sinai Medical Center, USA
Karen O’Connor, University of Pennsylvania, USA
Raul Rodriguez-Esteban, Roche Pharmaceuticals, Switzerland
Lucia Schmidt, Roche Pharmaceuticals, Switzerland
Juan M. Banda, Georgia State University, USA
Abeed Sarker, Emory University, USA
Yuting Guo, Emory University, USA
Yao Ge, Emory University, USA
Elena Tutubalina, Insilico Medicine, Hong Kong
Luis Gasco, Barcelona Supercomputing Center, Spain
Darryl Estrada, Barcelona Supercomputing Center, Spain
Martin Krallinger, Barcelona Supercomputing Center, Spain

Program Committee
Cecilia Arighi, University of Delaware, USA
Natalia Grabar, French National Center for Scientific Research, France
Thierry Hamon, Paris-Nord University, France
Antonio Jimeno Yepes, Royal Melbourne Institute of Technology, Australia
Jin-Dong Kim, Database Center for Life Science, Japan
Corrado Lanera, University of Padova, Italy
Robert Leaman, US National Library of Medicine, USA
Kirk Roberts, University of Texas Health Science Center at Houston, USA
Yutaka Sasaki, Toyota Technological Institute, Japan
Pierre Zweigenbaum, French National Center for Scientific Research, France


All questions should be emailed to Davy Weissenbacher (

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