A Unified Framework for Understanding and Intervening on False News Sharing

• DOI: 10.31234/osf.io/pxn29
• Publication Date: 2024-03-19T18:27:35Z
• Authors: Anton Gollwitzer; Alan Novaes Tump; Cameron Martel; Dominik Deffner; Mubashir Sultan; Ralf Kurvers; Ralph Hertwig
• Keywords: Fake News

False news can manipulate public opinion and undermine the credibility of legitimate newssources. Although many studies have examined sharing false news, there has been nocomprehensive, comparative, computational investigation interventions that reducethis harmful behavior. To do so, we introduce apply Dynamic Semi-Integrative Approach(DSIA). DSIA involves testing multiple interventions, individual- item-level effect modifiers,and choice modeling (drift–diffusion modeling) in a single framework. By applyingDSIA to find warning labels media literacy are particularlyeffective at increasing quality, followed by social norm intervention. Accuracyprompts were least effective. Intervention effects consistent across item-levelcharacteristics, such as age, analytical thinking, political-lean items, suggestingwide applicability. The operated via different decision-making processes, suggestingthat each intervention engages distinct mental processes attenuate sharing. Bydeveloping applying DSIA, provide uniquely detailed insight into newsinterventions, establish promising, scalable approach for future experimentalresearch theory development.