On channels such as Facebook, Twitter, and Instagram, users usually see what friends and acquaintances share from their personal network - for example as likes or retweets. Content that is shared in that way is very like to be distributed further.
“One of the reasons for that is that the sharing of such content within one’s personal network is seen as ‘usual’ and ‘normal’ thanks to the confirmation of others. Sometimes there is even the expectation to also then receive likes,” explains Professor Schüz from the Faculty of Human and Health Sciences at the University of Bremen. The pointing out of the questionable truth factor of certain content, which social media outlets such as Twitter now do, has not been able to curb this behavior.
The interdisciplinary team led by the psychologist Professor Benjamin Schüz and Christopher Jones, as well as the computer scientists Johannes Schöning and Daniel Diethei has therefore transformed and expanded one of the most important social elements of the networks: “We have expanded the social processes that are so important in enabling social networks to work and added the option to provide targeted social feedback stating no further forwarding,” states Professor Benjamin Schüz when explaining the new approach. “Users therefore not only see what friends and acquaintances have liked or shared. They now also see how often content has in fact been seen but not been liked or shared.”
People Who Read Fake News but Do Not Share It Influence Others
According to Schüz, it has become clear that this has had an effect on the social norms of users. “They then feel it to be less acceptable to share misinformation. Thanks to the easy implementation, we believe there to be great potential to support the users in reducing the large quantity of fake news on social networks with the aid of this additional information.”
This is significant, as it is often the case with controversial issues - most recently the corona measures and vaccinations - that confusing or simply incorrect information is spread with immense speed on social media and thus influences the opinion-forming process and behavior of many users.
The team from the University of Bremen finds the results promising. In three studies with nearly 1,500 Twitter users, the researchers were able to show that this additional information led to far less cases of misinformation being spread.
Further Information:
A pre-print of the study: https://psyarxiv.com/v6fc9/
www.healthsciences.uni-bremen.de
www.lsc-digital-public-health.de/
Contact:
Prof. Dr. Benjamin Schüz
Department of Prevention and Health Promotion
Institute of Public Health and Nursing Research (IPP)
Faculty of Human and Health Sciences
University of Bremen
Phone: +49 421 218-68833
Email: benjamin.schuezprotect me ?!uni-bremenprotect me ?!.de
Christopher Jones
Scientific Assistant
Institute of Public Health and Nursing Research (IPP)
Phone: +49 421 218-68888
Email: jonesprotect me ?!uni-bremenprotect me ?!.de
