Expressions of Loss Predict Aggressive Comments on Twitter Among Gang-involved Youth in Chicago

Patton, Desmond Upton; Rambow, Owen; Auerbach, Jonathan; Li, Kevin; Frey, William
npj Digital Medicine

Recent studies suggest social media shapes the transmission of firearm violence in high-poverty, urban neighborhoods. However, the exact pathways by which content on social media becomes threatening has not been studied. We consider a dataset of tweets by gang-involved Chicago youth that are coded for expressions of aggression and/or loss. Using a permutation test and mixed-effects log linear regression, we find that aggression and loss tweets do not occur randomly, and furthermore that in a 2-day window after loss expressions we find an increase in aggressive tweets. We discuss implications for intervention.