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. 2021 Mar 16;23(3):e23970. doi: 10.2196/23970

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©Wenhui Liu, Zhiru Wei, Xu Cheng, Ran Pang, Han Zhang, Guangshuai Li. Originally published in the Journal of Medical Internet Research (http://www.jmir.org), 16.03.2021.

This is an open-access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in the Journal of Medical Internet Research, is properly cited. The complete bibliographic information, a link to the original publication on http://www.jmir.org/, as well as this copyright and license information must be included.

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(A) Overall tweet sentiments in the three different phases. A negative number indicates negative sentiment, and a positive number indicates positive sentiment. (B) Total numbers and constituent ratios (labels in cells) of sentiments in different phases. (C) Sentiments for specific procedures. (D) Sentiments for tweets in which mentions of the procedures do or do not co-occur with mentions of COVID-19 in phases 2 and 3. *P<.05, **P<.01, ***P<.001.