Temporal communication dynamics in the aftermath of large-scale upheavals: do digital footprints reveal a stage model?

It has long been theorized that the exchange of information in the aftermath of large-scale upheavals ensues dynamics that follow a stage model, which would be a societal equivalent of individuals’ psychological processing of traumatic events. Nowadays, a relevant portion of this informational exchange occurs on social media platforms. In this study, we use the digital footprint of three independent earthquakes to analyze their communication dynamics. We find empirical evidence of a stage model previously proposed by Pennebaker (Pennebaker in Handbook of mental control, Prentice-Hall Inc., Hoboken, 1993) in the aftermath of the earthquakes. In addition, we further explore the role of emotions within the model stages through time using natural language processing tools. Our results show that emotions with low activation levels, such as interest and sadness, are expressed in higher proportions and are the most useful for predicting the expression of emotions with higher activation levels. Employing newly available computational methods like digital trace data, natural language processing, clustering, and causal analysis, this study extends Pennebaker’s model from offline to online social communication.