About the PIL Covid-19 series

Abstract: This two-part series is about the shape and flow of U.S. media coverage about Covid-19, and its visual representation across time and digital space during the early months of 2020. Included in Report 1 are interactive data visualizations showing the results of a computational analysis of 125,696 news articles from 66 widely-read national, metropolitan, and digital-only news websites. A follow-up analysis identifies the top 12 news outlets producing the most coverage (N=74,737) of Covid-19. Findings indicated the U.S. coronavirus news story gained momentum in three distinct waves of coverage that culminated in a news tsunami in mid-March that spread through every news section from business and politics to health and sports. Certain stories were amplified and re-circulated across news sites and on social media, thus creating a network of diverse contributors to this vast news ecosystem. In Report 2, a content analysis of 532 randomly selected news images from the top 12 outlets examined the visual representation of the coronavirus story. Five dominant visual themes – fear, hope, loneliness, determination, and grief – emerged from the sample of news images analyzed. Together, this series illustrates how the coronavirus story developed and spread, and how news is experienced in the 21st century, even as mass layoffs, mergers, and closures challenge the news industry. Applying a critical lens to how the news constructs our understanding of events develops information agency and makes individuals more discerning news consumers. Teaching and learning resources for librarians, educators, students, and journalists that make use of interactive news datasets and information visualizations from the series are included for building students’ news and visual literacy skills.

Preferred citation format: Alison J. Head, Steven Braun, Margy MacMillan, Jessica Yurkofsky, and Alaina C. Bull, September 15, 2020, Covid-19: The first 100 days of U.S. news coverage: Lessons about the media ecosystem for librarians, educators, students, and journalists, Project Information Literacy Research Institute, https://projectinfolit.org/publications/covid-19-the-first-100-days/.

About PIL

Project Information Literacy (PIL) is a nonprofit research institute in the San Francisco Bay Area. Since 2009, in a series of 12 groundbreaking scholarly research studies, PIL has investigated how U.S. college students and recent graduates utilize research skills, information competencies, and strategies for completing course work, engaging with news, and solving information problems in their everyday lives and the workplace. Research findings and recommendations from PIL studies and scholarly articles have informed and influenced the thinking and practices of diverse constituencies from all over the world in higher education, public libraries, newspapers, and the workplace. The latest release from PIL is a timely two-part series on U.S. Covid-19 news coverage during the first 100 days of 2020, which includes learning resources for building students’ news and visual literacy skills.

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@projectinfolit

Covid-19 series team

Principal Investigator
Alison J. Head, Ph.D.
PIL, Executive Director
Senior Researcher, metaLAB (at) Harvard
alison@projectinfolit.org


Co-Investigators
Steven Braun
PIL Fellow in Information Design
Visiting Assistant Professor in the College of Arts,
Media and Design, Northeastern University

Margy MacMillan
PIL, Senior Researcher
Emerita Professor, Mount Royal University, Canada

Alaina Bull
PIL, Research Analyst
First Year Experience Librarian, The University of
Washington Tacoma

Jessica Yurkofsky
PIL, Research Analyst
Creative technologist, Principal, metaLab [at] Harvard


Reviewing and Editing
Erica DeFrain
Barbara Fister
Jena Gaines
Meg McConahey


The Covid-19 U.S. news coverage series has a Creative Commons (CC) license of “CC BY-NCSA 4.0.” This license allows others to share, copy, adapt, and build upon the series’ findings and learning resources noncommercially, as long as the source — Project Information Literacy — is credited and users license their new creations under the identical terms.

Creative Commons attribution