Pandemic News: Facebook Pages of Mainstream News Media and the Coronavirus Crisis -- A Computational Content Analysis
May 27, 2020 Β· Declared Dead Β· π arXiv.org
"No code URL or promise found in abstract"
Evidence collected by the PWNC Scanner
Authors
Thorsten Quandt, Svenja Boberg, Tim Schatto-Eckrodt, Lena Frischlich
arXiv ID
2005.13290
Category
cs.SI: Social & Info Networks
Citations
38
Venue
arXiv.org
Last Checked
6 months ago
Abstract
The unfolding of the COVID-19 pandemic has been an unprecedented challenge for news media around the globe. While journalism is meant to process yet unknown events by design, the dynamically evolving situation affected all aspects of life in such profound ways that even the routines of crisis reporting seemed to be insufficient. Critics noted tendencies to horse-race reporting and uncritical coverage, with journalism being too close to official statements and too affirmative of political decisions. However, empirical data on the performance of journalistic news media during the crisis has been lacking thus far. The current study analyzes the Facebook messages of journalistic news media during the early Coronavirus crisis, based on a large German data set from January to March 2020. Using computational content analysis methods, reach and interactions, topical structure, relevant actors, negativity of messages, as well as the coverage of fabricated news and conspiracy theories were examined. The topical structure of the near-time Facebook coverage changed during various stages of the crisis, with just partial support for the claims of critics. The initial stages were somewhat lacking in topical breadth, but later stages offered a broad range of coverage on Corona-related issues and societal concerns. Further, journalistic media covered fake news and conspiracy theories during the crisis, but they consistently contextualized them as what they were and debunked the false claims circulating in public. While some criticism regarding the performance of journalism during the crisis received mild empirical support, the analysis did not find overwhelming signs of systemic dysfunctionalities. Overall, journalistic media did not default to a uniform reaction nor to sprawling, information-poor pandemic news, but they responded with a multi-perspective coverage of the crisis.
Community Contributions
Found the code? Know the venue? Think something is wrong? Let us know!
π Similar Papers
In the same crypt β Social & Info Networks
R.I.P.
π»
Ghosted
R.I.P.
π»
Ghosted
Fake News Detection on Social Media: A Data Mining Perspective
R.I.P.
π»
Ghosted
Natural Scales in Geographical Patterns
R.I.P.
π»
Ghosted
Representation Learning on Graphs: Methods and Applications
R.I.P.
π»
Ghosted
The COVID-19 Social Media Infodemic
R.I.P.
π»
Ghosted
OSMnx: New Methods for Acquiring, Constructing, Analyzing, and Visualizing Complex Street Networks
Died the same way β π» Ghosted
R.I.P.
π»
Ghosted
Federated Learning: Strategies for Improving Communication Efficiency
R.I.P.
π»
Ghosted
In-Datacenter Performance Analysis of a Tensor Processing Unit
R.I.P.
π»
Ghosted
Deep Convolutional Neural Networks for Computer-Aided Detection: CNN Architectures, Dataset Characteristics and Transfer Learning
R.I.P.
π»
Ghosted