Softly empowering a prosocial expert in the family: lasting effects of a counter-misinformation intervention in an informational autocracy.

The present work is the first to comprehensively analyze the gravity of the misinformation problem in Hungary, where misinformation appears regularly in the pro-governmental, populist, and socially conservative mainstream media. In line with international data, using a Hungarian representative sample (Study 1, N = 991), we found that voters of the reigning populist, conservative party could hardly distinguish fake from real news. In Study 2, we demonstrated that a prosocial intervention of ~ 10 min (N = 801) helped young adult participants discern misinformation four weeks later compared to the control group without implementing any boosters.

A scoping review on the use of natural language processing in research on political polarization: trends and research prospects.

Unlabelled: As part of the "text-as-data" movement, Natural Language Processing (NLP) provides a computational way to examine political polarization. We conducted a methodological scoping review of studies published since 2010 ( = 154) to clarify how NLP research has conceptualized and measured political polarization, and to characterize the degree of integration of the two different research paradigms that meet in this research area. We identified biases toward US context (59%), Twitter data (43%) and machine learning approach (33%).