Reconstructing social sensitivity from evolution of content volume in Twitter

TL;DR

This paper presents a mathematical model linking media coverage and social interactions to public interest dynamics on Twitter during US violence events, revealing insights into social sensitivity and mobilization.

Contribution

The study introduces a simple mathematical model that connects media and social dynamics to measure social sensitivity from Twitter data.

Findings

Model successfully fits Twitter and news data during violence events.

Inferred social sensitivity correlates with human mobility data.

Insights into mechanisms driving social mobilizations.

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.