The proliferation of false and misleading news on social media and news outlets has been a cause of concern for a number of years. And with every election that passes, and with each additional wave of the COVID-19 pandemic, these concerns are only growing, and growing fast. It is therefore of the utmost importance to better understand why people share misinformation, and to seek solutions to reduce this sharing. Research done thus far has produced evidence that people often value partisanship over accuracy, which is why information, even if false, proliferates. Partisanship in turn facilitates the formation of echo chambers, where false information reverberates, appearing more and more truer to the party as time goes by. To the contrary, however, research has also shown that people often share misinformation simply because their attention is focused on factors other than accuracy, such as partisanship, and that thus subtle nudges towards attention to accuracy might increase the quality of news that people share. But attention-based interventions require cooperation, i.e., selfless acts of tagging, rating, or attaching warnings or comments to information, and doing so for the greater good. Public cooperation is always a difficult proposition because people are often selfish, and in this case it is also prone to error and misjudgment. Thus, even with the best intentions, combating misinformation remains a formidable challenge in modern human societies.
With the launch of the Misinformation and Cooperation Editor’s Challenge, we wish to give space to research that explores what methods of physics and network science can contribute towards our better understanding of misinformation propagation, echo chamber formation, and information spreading over social networks. We also welcome research that explores how and to what degree human cooperation can facilitate the reduction of sharing false information, and what role algorithms and artificial intelligence play in making social media and news outlets more trustworthy and reliable. Comparisons of different approaches aimed either at identifying or suppressing the sharing of misinformation, be it through human experiments or mathematical models, are also most welcome.
With these goals in mind, possible topics in relation to misinformation and false news include, but are not limited to:
- Misinformation detection
- Information cascades and propagation
- Community and echo chamber formation
- Network dismantling and immunization
- Algorithms and artificial intelligence
- Promotion of public cooperation
- Higher-order social networks
- Multilayer networks
We are keen to receive critical, ambitious, and courageous contributions to these and related topics with the common goal of addressing the Editor's Challenge on Misinformation and Cooperation.
The Specialty Chief Editors of Frontiers in Physics launch a new series of Research Topics to highlight current challenges across the field of Physics. Other titles in the series are
Editor's Challenge in Radiation Detectors and Imaging: Emerging Technologies
Editor’s Challenge in Atomic and Molecular Physics: Applications and Advances in Fundamental Physics
Editor's Challenge in Interdisciplinary Physics: What is Interdisciplinary Physics?
Editor's Challenge in Quantum Engineering and Technology: Economic Impact and Perspectives of Quantum Technologies
Editor's Challenge in Optics and Photonics: Advancing Electronics with Photonics
