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

#SMM4H 2022

Data Mining & Analysis

First call for papers, submission deadline is August 15, 2022
First 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: https://healthlanguageprocessing.org/smm4h-2022/
Submission link: TBA
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 (https://coling2022.org/index), invites 4-page paper (unlimited references in standard COLING format) submissions on original, unpublished research in all aspects at the intersection of social media mining and health.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 https://healthlanguageprocessing.org/smm4h-2022/
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, University of Pennsylvania, USA
Davy Weissenbacher, University of Pennsylvania, USA
Arjun Magge, University of Pennsylvania, USA
Ari Z. Klein, University of Pennsylvania, USA
Ivan Flores, University of Pennsylvania, 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
All questions should be emailed to Davy Weissenbacher (dweissen@pennmedicine.upenn.edu)