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#SMM4H: Social Media Mining for Health Applications Workshop & Shared Task at ACL 2019
Location: Florence, Italy
Date: August 2, 2019
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Call for papers
Call for shared task participation
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* Apologies if you received multiple copies of this CFP *
Important links:
Workshop: https://healthlanguageprocessing.org/smm4h/
Submission link: https://www.softconf.com/acl2019/smm4h/
Shared task details: https://healthlanguageprocessing.org/smm4h/challenge/
Workshop
This workshop aims to provide a forum for the ACL community members to present and discuss NLP advances specific to social media use in the particularly challenging area of health-related research and applications, following on the success of the third iteration of #SMM4H at EMNLP in 2018. The workshop seeks to attract researchers interested in novel automatic approaches for the large-scale collection, extraction, representation, analysis, and validation of social media data for monitoring and surveillance.
The workshop will include two components—a standard workshop and a shared task:
Workshop/research forum component: For this component, we invite extended abstracts of 2-4 pages (not including references) and paper submissions of 4-8 pages (not including references) in standard ACL format. Please see submission guidelines below. 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 and classifying 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 and disease progression studies using social media
Sentinel event detection using social media
Semantic methods in social media analysis relevant to health research
Classifying health-related messages in social media
Cohort identification from publicly available social media data
Automatic analysis of social media messages for disease surveillance and patient education
Methods for validation of social-media derived hypothesis and datasets
Shared task component: Details about the shared task can be found at the Shared Task Website. Best performing teams will be invited to submit system description papers at the workshop.
Important dates
Paper submission deadline: April 26, 2019
Notification of acceptance: May 24, 2019
Camera-ready version due: June 3, 2019
Workshop date: August 2, 2019
The shared tasks will follow a different schedule, as explained in the shared task website (https://healthlanguageprocessing.org/smm4h/challenge/).
Submission Guidelines
All workshop papers must be original and not simultaneously submitted to another journal or conference. All papers focusing on natural language processing of social media texts for health-related tasks are welcome.
Full papers must have a maximum length of 4-8 pages (plus references)
Extended Abstracts may have a maximum length of 2-4 pages (plus references)
System Descriptions (shared task participants only) may have a maximum of 2 pages (plus references). Accepted system descriptions will also be included in the workshop proceedings.
Please follow the standard submission guidelines of ACL 2019 available here: http://www.acl2019.org/EN/call-for-papers.xhtml
All submissions must be through Softconf. Submission link: https://www.softconf.com/acl2019/smm4h/
Organizing Committee
Chair - Graciela Gonzalez-Hernandez, University of Pennsylvania
Co-chair - Davy Weissenbacher, University of Pennsylvania
Michael Paul, University of Colorado-Boulder
Abeed Sarker, University of Pennsylvania
Ari Klein, University of Pennsylvania
Ashlynn Daughton, University of Colorado-Boulder
Karen O’Connor, University of Pennsylvania
Program Committee
Nigel Collier, University of Cambridge, UK
Larry Hunter, University of Colorado, USA
Hongfang Liu, Mayo Clinic Rochester, USA
Pierre Zweigenbaum, French National Center for Scientific Research, France
Cecile Paris, CSIRO, Australia
Kirk Roberts, University of Texas Houston, USA
Robert Leaman, US National Library of Medicine, USA
Azadeh Nikfarjam, Nuance Communication, USA
Ehsan Emazadeh, Google Inc., USA
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