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Title: Understanding Local News Social Coverage and Engagement at Scale during the COVID-19 Pandemic
During the COVID-19 pandemic, local news organizations have played an important role in keeping communities informed about the spread and impact of the virus. We explore how political, social media, and economic factors impacted the way local media reported on COVID-19 developments at a national scale between January 2020 and July 2021. We construct and make available a dataset of over 10,000 local news organizations and their social media handles across the U.S. We use social media data to estimate the population reach of outlets (their “localness”), and capture underlying content relationships between them. Building on this data, we analyze how local and national media covered four key COVID-19 news topics: Statistics and Case Counts, Vaccines and Testing, Public Health Guidelines, and Economic Effects. Our results show that news outlets with higher population reach reported proportionally more on COVID-19 than more local outlets. Separating the analysis by topic, we expose more nuanced trends, for example that outlets with a smaller population reach covered the Statistics and Case Counts topic proportionally more, and the Economic Effects topic proportionally less. Our analysis further shows that people engaged proportionally more and used stronger reactions when COVID-19 news were posted by outlets with a smaller population reach. Finally, we demonstrate that COVID-19 posts in Republican-leaning counties generally received more comments and fewer likes than in Democratic counties, perhaps indicating controversy.  more » « less
Award ID(s):
1840751
NSF-PAR ID:
10379039
Author(s) / Creator(s):
; ;
Date Published:
Journal Name:
Proceedings of the International AAAI Conference on Web and Social Media
Volume:
16
ISSN:
2162-3449
Page Range / eLocation ID:
560 to 572
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
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