Face-to-Face Encounters Trump Digital Networks in Predicting Election Outcomes, Research Reveals
Physical co-location patterns predict county-level voting behavior with remarkable 97% accuracy, according to new research. The findings challenge assumptions about digital networks’ political influence and highlight the enduring power of real-world interactions. Offline social ties demonstrated stronger effects on individual voter choices than online connections.
Groundbreaking Study Reveals Physical Interactions Outperform Digital Networks
Real-world social encounters predict voting patterns with significantly greater accuracy than online social networks or residential proximity, according to a new study published in PNAS Nexus. The research, conducted by Michele Tizzoni and colleagues, analyzed massive-scale co-location data from Meta’s Data for Good program, which collects anonymized location information from Facebook users who enabled location services.
