Replication Data for: Multi-party Media Partisanship Attention Score: estimating partisan attention of news media sources using Twitter data in the lead up of the 2018 Italian election

The ongoing radical transformations in communication ecosystems have brought up renowned concerns about the risks of partisan selective exposure and ideological polarization. Traditionally, partisan selective exposure is measured by cross-tabulating survey responses on respondents vote intentions and media consumption. This process is expensive, limits the number of news outlets taken into account and prone to the typical biases of self-reported data. Building upon previous works and with a specific focus on the online media environment, we introduce a new method to measure media partisanship attention in a multi-party political system using Twitter data from 2018 Italian general election. Our first research question addresses the effectiveness of this method by measuring the extent to which our estimates correlate with partisan newspaper consumption measured by the latest Italian National Election Studies (ITANES) survey. Once established the reliability of our method, we employ these scores and measures to analyze the Italian digital media ecosystem in the lead of March 2018 election. The traditionally high level of political parallelism that characterizes both the Italian press and TV sectors is only partially reflected in a digital media ecosystem where partisan news sources seem to coexist with cross-partisan outlets. Results also point out that certain online partisan communities tend to rely more on exclusive news media sources. Reference Fabio Giglietto, Nicola Righetti, Giada Marino, Luca Rossi, Multi-Party Media Partisanship Attention Score. Estimating Partisan Attention of News Media Sources Using Twitter Data in the Lead-up to 2018 Italian Election, in "Comunicazione politica, Quadrimestrale dell'Associazione Italiana di Comunicazione Politica" 1/2019, pp. 85-108, doi: 10.3270/93030