This paper is in the following e-collection/theme issue:

Medicine 2.0: Social Media, Open, Participatory, Collaborative Medicine (1739) New Methods (1003) Occupational Health and Ergonomics/Prevention at the Workplace (251) Natural Language Processing (763)

Published on in Vol 22, No 8 (2020): August

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/19222, first published .
Topic Modeling of Social Networking Service Data on Occupational Accidents in Korea: Latent Dirichlet Allocation Analysis

Topic Modeling of Social Networking Service Data on Occupational Accidents in Korea: Latent Dirichlet Allocation Analysis

Topic Modeling of Social Networking Service Data on Occupational Accidents in Korea: Latent Dirichlet Allocation Analysis

Authors of this article:

Kyoung-Bok Min1 Author Orcid Image ;   Sung-Hee Song1 Author Orcid Image ;   Jin-Young Min2 Author Orcid Image
Article Authors Cited by (16) Tweetations (3) Metrics
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doctick doctick @doctick

#NLP "Topic modeling of social networking service data on occupational accidents: LDA analysis." https://t.co/NdMhbLNunL

11:22 AM · Jul 15, 2020

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Sven Awege Sven Awege @SVENNIECO

Topic Modeling of Social Networking Service Data on Occupational Accidents in Korea: Latent Dirichlet Allocation An… https://t.co/yY5PJmpPyc

2:10 PM · Aug 13, 2020

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JMIR Publications JMIR Publications @jmirpub

New in JMIR: Topic Modeling of Social Networking Service Data on Occupational Accidents in Korea: Latent Dirichlet… https://t.co/5DPwJRleoC

2:34 PM · Aug 13, 2020

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