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Engagement With COVID-19 Public Health Measures in the United States: A Cross-sectional Social Media Analysis from June to November 2020.
Massey, Daisy; Huang, Chenxi; Lu, Yuan; Cohen, Alina; Oren, Yahel; Moed, Tali; Matzner, Pini; Mahajan, Shiwani; Caraballo, César; Kumar, Navin; Xue, Yuchen; Ding, Qinglan; Dreyer, Rachel; Roy, Brita; Krumholz, Harlan.
  • Massey D; Center for Outcomes Research and Evaluation, Yale New Haven Hospital, New Haven, CT, United States.
  • Huang C; Center for Outcomes Research and Evaluation, Yale New Haven Hospital, New Haven, CT, United States.
  • Lu Y; Center for Outcomes Research and Evaluation, Yale New Haven Hospital, New Haven, CT, United States.
  • Cohen A; Section of Cardiovascular Medicine, Department of Internal Medicine, Yale School of Medicine, New Haven, CT, United States.
  • Oren Y; Signals Analytics, New York, NY, United States.
  • Moed T; Signals Analytics, New York, NY, United States.
  • Matzner P; Signals Analytics, New York, NY, United States.
  • Mahajan S; Signals Analytics, New York, NY, United States.
  • Caraballo C; Center for Outcomes Research and Evaluation, Yale New Haven Hospital, New Haven, CT, United States.
  • Kumar N; Section of Cardiovascular Medicine, Department of Internal Medicine, Yale School of Medicine, New Haven, CT, United States.
  • Xue Y; Center for Outcomes Research and Evaluation, Yale New Haven Hospital, New Haven, CT, United States.
  • Ding Q; Section of Cardiovascular Medicine, Department of Internal Medicine, Yale School of Medicine, New Haven, CT, United States.
  • Dreyer R; Department of Sociology, Yale University, New Haven, CT, United States.
  • Roy B; Foundation for a Smoke-Free World, New York, NY, United States.
  • Krumholz H; College of Health and Human Sciences, Purdue University, West Lafayette, IN, United States.
J Med Internet Res ; 23(6): e26655, 2021 06 21.
Article in English | MEDLINE | ID: covidwho-1259299
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ABSTRACT

BACKGROUND:

COVID-19 has continued to spread in the United States and globally. Closely monitoring public engagement and perceptions of COVID-19 and preventive measures using social media data could provide important information for understanding the progress of current interventions and planning future programs.

OBJECTIVE:

The aim of this study is to measure the public's behaviors and perceptions regarding COVID-19 and its effects on daily life during 5 months of the pandemic.

METHODS:

Natural language processing (NLP) algorithms were used to identify COVID-19-related and unrelated topics in over 300 million online data sources from June 15 to November 15, 2020. Posts in the sample were geotagged by NetBase, a third-party data provider, and sensitivity and positive predictive value were both calculated to validate the classification of posts. Each post may have included discussion of multiple topics. The prevalence of discussion regarding these topics was measured over this time period and compared to daily case rates in the United States.

RESULTS:

The final sample size included 9,065,733 posts, 70% of which were sourced from the United States. In October and November, discussion including mentions of COVID-19 and related health behaviors did not increase as it had from June to September, despite an increase in COVID-19 daily cases in the United States beginning in October. Additionally, discussion was more focused on daily life topics (n=6,210,255, 69%), compared with COVID-19 in general (n=3,390,139, 37%) and COVID-19 public health measures (n=1,836,200, 20%).

CONCLUSIONS:

There was a decline in COVID-19-related social media discussion sourced mainly from the United States, even as COVID-19 cases in the United States increased to the highest rate since the beginning of the pandemic. Targeted public health messaging may be needed to ensure engagement in public health prevention measures as global vaccination efforts continue.
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Full text: Available Collection: International databases Database: MEDLINE Main subject: Public Health / Social Media / COVID-19 Type of study: Observational study / Prognostic study / Randomized controlled trials Topics: Vaccines Limits: Humans Country/Region as subject: North America Language: English Journal: J Med Internet Res Journal subject: Medical Informatics Year: 2021 Document Type: Article Affiliation country: 26655

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Full text: Available Collection: International databases Database: MEDLINE Main subject: Public Health / Social Media / COVID-19 Type of study: Observational study / Prognostic study / Randomized controlled trials Topics: Vaccines Limits: Humans Country/Region as subject: North America Language: English Journal: J Med Internet Res Journal subject: Medical Informatics Year: 2021 Document Type: Article Affiliation country: 26655