Social media mining shared task workshop

Abeed Sarker, Azadeh Nikfarjam, Graciela Gonzalez

Research output: Chapter in Book/Report/Conference proceedingConference proceeding contribution

30 Citations (Scopus)
7 Downloads (Pure)

Abstract

Social media has evolved into a crucial resource for obtaining large volumes of real-time information. The promise of social media has been realized by the public health domain, and recent research has addressed some important challenges in that domain by utilizing social media data. Tasks such as monitoring flu trends, viral disease outbreaks, medication abuse, and adverse drug reactions are some examples of studies where data from social media have been exploited. The focus of this workshop is to explore solutions to three important natural language processing challenges for domain-specific social media text: (i) text classification, (ii) information extraction, and (iii) concept normalization. To explore different approaches to solving these problems on social media data, we designed a shared task which was open to participants globally. We designed three tasks using our in-house annotated Twitter data on adverse drug reactions. Task 1 involved automatic classification of adverse drug reaction assertive user posts; Task 2 focused on extracting specific adverse drug reaction mentions from user posts; and Task 3, which was slightly ill-defined due to the complex nature of the problem, involved normalizing user mentions of adverse drug reactions to standardized concept IDs. A total of 11 teams participated, and a total of 24 (18 for Task 1, and 6 for Task 2) system runs were submitted. Following the evaluation of the systems, and an assessment of their innovation/novelty, we accepted 7 descriptive manuscripts for publication— 5 for Task 1 and 2 for Task 2. We provide descriptions of the tasks, data, and participating systems in this paper.

Original languageEnglish
Title of host publicationBiocomputing 2016
Subtitle of host publicationProceedings of the Pacific Symposium
EditorsRuss B. Altman, A. Keith Dunker, Lawrence Hunter, Marylyn D. Ritchie, Tiffany Murray, Teri E. Klein
Place of PublicationSingapore
PublisherWorld Scientific Publishing
Pages581-592
Number of pages12
ISBN (Electronic)9789814749428
ISBN (Print)9789814749404
DOIs
Publication statusPublished - 2016
Externally publishedYes
Event21st Pacific Symposium on Biocomputing, PSB 2016 - Kohala Coast, United States
Duration: 4 Jan 20168 Jan 2016

Publication series

NamePacific Symposium on Biocomputing. Pacific Symposium on Biocomputing
ISSN (Print)2335-6928

Conference

Conference21st Pacific Symposium on Biocomputing, PSB 2016
CountryUnited States
CityKohala Coast
Period4/01/168/01/16

Bibliographical note

Copyright the Publisher 2016. Version archived for private and non-commercial use with the permission of the author/s and according to publisher conditions. For further rights please contact the publisher.

Keywords

  • Concept Extraction
  • Text Classification
  • Adverse Drug Reaction
  • Pharmacovigilance
  • Social Media Mining

Fingerprint Dive into the research topics of 'Social media mining shared task workshop'. Together they form a unique fingerprint.

  • Cite this

    Sarker, A., Nikfarjam, A., & Gonzalez, G. (2016). Social media mining shared task workshop. In R. B. Altman, A. K. Dunker, L. Hunter, M. D. Ritchie, T. Murray, & T. E. Klein (Eds.), Biocomputing 2016: Proceedings of the Pacific Symposium (pp. 581-592). (Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing). Singapore: World Scientific Publishing. https://doi.org/10.1142/9789814749411_0054