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

JMIR Theme Issue: COVID-19 Special Issue (2242) Infodemiology and Infoveillance (1127) Medicine 2.0: Social Media, Open, Participatory, Collaborative Medicine (1402) Infoveillance, Infodemiology, Digital Disease Surveillance, Infodemic Management (923) Outbreak and Pandemic Preparedness and Management (1530) Theme Issue: Novel Coronavirus (COVID-19) Outbreak Rapid Reports (1385)

Published on in Vol 22 , No 11 (2020) :November

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/21504, first published .
Communicative Blame in Online Communication of the COVID-19 Pandemic: Computational Approach of Stigmatizing Cues and Negative Sentiment Gauged With Automated Analytic Techniques

Communicative Blame in Online Communication of the COVID-19 Pandemic: Computational Approach of Stigmatizing Cues and Negative Sentiment Gauged With Automated Analytic Techniques

Communicative Blame in Online Communication of the COVID-19 Pandemic: Computational Approach of Stigmatizing Cues and Negative Sentiment Gauged With Automated Analytic Techniques

Authors of this article:

Angela Chang 1, 2 Author Orcid Image ;   Peter Johannes Schulz 2 Author Orcid Image ;   ShengTsung Tu 3 Author Orcid Image ;   Matthew Tingchi Liu 4 Author Orcid Image
Article Authors Cited by (18) Tweetations (4) Metrics

Journals

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  16. Chang A, Schulz P, Jiao W, Liu M. Obesity-Related Communication in Digital Chinese News From Mainland China, Hong Kong, and Taiwan: Automated Content Analysis. JMIR Public Health and Surveillance 2021;7(11):e26660 View
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