During the COVID-19 pandemic, local news organizations have played an integral 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 have reported on COVID-19 developments at a national scale. We construct and make available a dataset of over 10,000 local news organizations across the U.S. and their social media handles. We use social media data to model the population reach of outlets, and the 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 have reported proportionally more on COVID-19 than more local outlets. When broken out by topic, we observe that the Statistics and Case Counts topic is covered proportionally more by outlets that have a lower population reach and are in more Republican-leaning areas, an effect which is re- versed for the Economic Effects topic. Our analysis further shows that while social media audiences generally engage less with outlets with a smaller population reach, they tend to engage more with these outlets on posts about COVID-19. People also use relatively more emotive reactions on the posts of low population reach outlets. Finally, we demonstrate that COVID-19 posts in Republican-leaning counties generally receive more comments and fewer likes than in Democratic counties.

Understanding Local News Social Coverage and Engagement at Scale During the COVID-19 Pandemic

s1-4: Social Media Behavior 1

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The International AAAI Conference on Web and Social Media (ICWSM) is a forum for researchers from multiple disciplines to come together to share knowledge, discuss ideas, exchange information, and learn about cutting-edge research in diverse fields with the common theme of online social media. This overall theme includes research in new perspectives in social theories, as well as computational algorithms for analyzing social media. ICWSM is a singularly fitting venue for research that blends social science and computational approaches to answer important and challenging questions about human social behavior through social media while advancing computational tools for vast and unstructured data.


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ICWSM 2022

The International AAAI Conference on Web and Social Media (ICWSM) is a forum for researchers from multiple disciplines to come together to share knowledge, discuss ideas, exchange information, and learn about cutting-edge research in diverse fields with the common theme of online social media. This overall theme includes research in new perspectives in social theories, as well as computational algorithms for analyzing social media. ICWSM is a singularly fitting venue for research that blends social science and computational approaches to answer important and challenging questions about human social behavior through social media while advancing computational tools for vast and unstructured data.

Marianne Aubin Le Quéré

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Understanding Local News Social Coverage and Engagement at Scale During the COVID-19 Pandemic

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