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J. Med. Internet Res. · Aug 2020
Social Network Analysis of COVID-19 Sentiments: Application of Artificial Intelligence.
- Man Hung, Evelyn Lauren, Eric S Hon, Wendy C Birmingham, Julie Xu, Sharon Su, Shirley D Hon, Jungweon Park, Peter Dang, and Martin S Lipsky.
- College of Dental Medicine, Roseman University of Health Sciences, South Jordan, UT, United States.
- J. Med. Internet Res. 2020 Aug 18; 22 (8): e22590.
BackgroundThe coronavirus disease (COVID-19) pandemic led to substantial public discussion. Understanding these discussions can help institutions, governments, and individuals navigate the pandemic.ObjectiveThe aim of this study is to analyze discussions on Twitter related to COVID-19 and to investigate the sentiments toward COVID-19.MethodsThis study applied machine learning methods in the field of artificial intelligence to analyze data collected from Twitter. Using tweets originating exclusively in the United States and written in English during the 1-month period from March 20 to April 19, 2020, the study examined COVID-19-related discussions. Social network and sentiment analyses were also conducted to determine the social network of dominant topics and whether the tweets expressed positive, neutral, or negative sentiments. Geographic analysis of the tweets was also conducted.ResultsThere were a total of 14,180,603 likes, 863,411 replies, 3,087,812 retweets, and 641,381 mentions in tweets during the study timeframe. Out of 902,138 tweets analyzed, sentiment analysis classified 434,254 (48.2%) tweets as having a positive sentiment, 187,042 (20.7%) as neutral, and 280,842 (31.1%) as negative. The study identified 5 dominant themes among COVID-19-related tweets: health care environment, emotional support, business economy, social change, and psychological stress. Alaska, Wyoming, New Mexico, Pennsylvania, and Florida were the states expressing the most negative sentiment while Vermont, North Dakota, Utah, Colorado, Tennessee, and North Carolina conveyed the most positive sentiment.ConclusionsThis study identified 5 prevalent themes of COVID-19 discussion with sentiments ranging from positive to negative. These themes and sentiments can clarify the public's response to COVID-19 and help officials navigate the pandemic.©Man Hung, Evelyn Lauren, Eric S Hon, Wendy C Birmingham, Julie Xu, Sharon Su, Shirley D Hon, Jungweon Park, Peter Dang, Martin S Lipsky. Originally published in the Journal of Medical Internet Research (http://www.jmir.org), 18.08.2020.
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