Reconstructing social sensitivity from evolution of content volume in Twitter

Abstract

We set up a simple mathematical model for the dynamics of public interest in terms of media coverage and social interactions. We test the model on a series of events related to violence in the US during 2020, using the volume of tweets and retweets as a proxy of public interest, and the volume of news as a proxy of media coverage. The model succesfully fits the data and allows inferring a measure of social sensibility that correlates with human mobility data. These findings suggest the basic ingredients and mechanisms that regulate social responses capable of ignite social mobilizations.

References in corpus (3)

• Statistical physics of social dynamics
• Novelty and Collective Attention
• Emergence of polarized ideological opinions in multidimensional topic spaces