Using Twitter Data to Estimate Partisan Attention in a Multi-Party Media System

It has just been published “Multi-Party Media Partisanship Attention Score. Estimating Partisan Attention of News Media Sources Using Twitter Data in the Lead-up to 2018 Italian Election”.

Extending the computational method first introduced by Benkler, Faris, Roberts and others (see here and here), the paper makes use of Twitter data to measure partisan attention to news media sources in a multi-party political system.

To validate the method we compared our results with those obtained through a survey (ITANES), finding remarkable similarity (see figure below).

Furthermore, we analyzed the degree of polarization of the Italian online news media system we observed in the lead-up to the 2018 Italian election, finding a moderate level of polarization.

We also find that populist parties’ online communities relied on news sources characterized by an higher level of insularity (i.e. mainly shared on Twitter by their partisan community only) than non-populist ones.

Replication data and R code used in the study can be found here, while the paper can be read here.