TY  - JOUR
AU  - Massey, Daisy
AU  - Huang, Chenxi
AU  - Lu, Yuan
AU  - Cohen, Alina
AU  - Oren, Yahel
AU  - Moed, Tali
AU  - Matzner, Pini
AU  - Mahajan, Shiwani
AU  - Caraballo, César
AU  - Kumar, Navin
AU  - Xue, Yuchen
AU  - Ding, Qinglan
AU  - Dreyer, Rachel
AU  - Roy, Brita
AU  - Krumholz, Harlan
PY  - 2021
DA  - 2021/6/21
TI  - Engagement With COVID-19 Public Health Measures in the United States: A Cross-sectional Social Media Analysis from June to November 2020
JO  - J Med Internet Res
SP  - e26655
VL  - 23
IS  - 6
KW  - COVID-19
KW  - public perception
KW  - social media
KW  - infodemiology
KW  - infoveillance
KW  - infodemic
KW  - social media research
KW  - social listening
KW  - social media analysis
KW  - natural language processing
KW  - Reddit data
KW  - Facebook data
KW  - COVID-19 public health measures
KW  - public health
KW  - surveillance
KW  - engagement
KW  - United States
KW  - cross-sectional
KW  - Reddit
KW  - Facebook
KW  - behavior
KW  - perception
KW  - NLP
AB  - 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. 
SN  - 1438-8871
UR  - https://www.jmir.org/2021/6/e26655
UR  - https://doi.org/10.2196/26655
UR  - http://www.ncbi.nlm.nih.gov/pubmed/34086593
DO  - 10.2196/26655
ID  - info:doi/10.2196/26655
ER  -