Tweet Classification Toward Twitter-Based Disease Surveillance: New Data, Methods, and Evaluations

Journal of Medical Internet Research
Shoko WakamiyaEiji Aramaki

Abstract

The amount of medical and clinical-related information on the Web is increasing. Among the different types of information available, social media-based data obtained directly from people are particularly valuable and are attracting significant attention. To encourage medical natural language processing (NLP) research exploiting social media data, the 13th NII Testbeds and Community for Information access Research (NTCIR-13) Medical natural language processing for Web document (MedWeb) provides pseudo-Twitter messages in a cross-language and multi-label corpus, covering 3 languages (Japanese, English, and Chinese) and annotated with 8 symptom labels (such as cold, fever, and flu). Then, participants classify each tweet into 1 of the 2 categories: those containing a patient's symptom and those that do not. This study aimed to present the results of groups participating in a Japanese subtask, English subtask, and Chinese subtask along with discussions, to clarify the issues that need to be resolved in the field of medical NLP. In summary, 8 groups (19 systems) participated in the Japanese subtask, 4 groups (12 systems) participated in the English subtask, and 2 groups (6 systems) participated in the Chinese subtask. In total, 2 ba...Continue Reading

References

Oct 29, 2008·Clinical Infectious Diseases : an Official Publication of the Infectious Diseases Society of America·Philip M PolgreenForrest D Nelson
Sep 6, 2014·BMC Health Services Research·Albert BoonstraJanita F J Vos
Feb 3, 2015·PLoS Currents·Michael J PaulDavid Broniatowski
Oct 3, 2018·JMIR Public Health and Surveillance·Shoko WakamiyaEiji Aramaki

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Citations

Apr 1, 2018·Journal of Biomedical Semantics·Aurélie NévéolPierre Zweigenbaum
May 31, 2019·Journal of Medical Internet Research·Victor Pereira-SanchezAlan Teo
Jan 7, 2021·International Journal of Environmental Research and Public Health·Ebtesam AlomariRashid Mehmood
Jun 18, 2021·Frontiers in Public Health·Miguel A Alvarez-MonCristina Lopez-Del Burgo

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Software Mentioned

learn
i2b2
TweetTokenizer
Doc
MedNLP
Twitter Developer
scikit
jieba
MeCab
macro

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