ITU

Multi-Party Media Partisanship Attention Score. Estimating Partisan Attention of News Media Sources Using Twitter Data in the Lead-up to 2018 Italian Election

Research output: Journal Article or Conference Article in Journal › Journal article › Research › peer-review

Standard

Multi-Party Media Partisanship Attention Score. Estimating Partisan Attention of News Media Sources Using Twitter Data in the Lead-up to 2018 Italian Election. / Giglietto, Fabio; Righetti, Nicola; Marino, Giada; Rossi, Luca.

In: Comunicazione Politica, 01.04.2019, p. 85-108.

Research output: Journal Article or Conference Article in Journal › Journal article › Research › peer-review

Harvard

Giglietto, F, Righetti, N, Marino, G & Rossi, L 2019, 'Multi-Party Media Partisanship Attention Score. Estimating Partisan Attention of News Media Sources Using Twitter Data in the Lead-up to 2018 Italian Election', Comunicazione Politica, pp. 85-108. https://doi.org/10.3270/93030

APA

Giglietto, F., Righetti, N., Marino, G., & Rossi, L. (2019). Multi-Party Media Partisanship Attention Score. Estimating Partisan Attention of News Media Sources Using Twitter Data in the Lead-up to 2018 Italian Election. Comunicazione Politica, 85-108. https://doi.org/10.3270/93030

Vancouver

Giglietto F, Righetti N, Marino G, Rossi L. Multi-Party Media Partisanship Attention Score. Estimating Partisan Attention of News Media Sources Using Twitter Data in the Lead-up to 2018 Italian Election. Comunicazione Politica. 2019 Apr 1;85-108. https://doi.org/10.3270/93030

Author

Giglietto, Fabio ; Righetti, Nicola ; Marino, Giada ; Rossi, Luca. / 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. 2019 ; pp. 85-108.

Bibtex

@article{ea280c2fac404049a745b1e127f8508e,
title = "Multi-Party Media Partisanship Attention Score. Estimating Partisan Attention of News Media Sources Using Twitter Data in the Lead-up to 2018 Italian Election",
abstract = "The ongoing radical transformations in communication ecosystems have brought up concerns about the risks of partisan selective exposure and ideological polarization. Traditionally, partisan selective exposure is measured by cross-tabulating survey responses to questions on vote intentions and media consumption. This process is expensive, limits the number of news outlets taken into account and is prone to the typical biases of self-reported data. Building upon previous works and with a specific focus on the online media...",
author = "Fabio Giglietto and Nicola Righetti and Giada Marino and Luca Rossi",
year = "2019",
month = apr,
day = "1",
doi = "10.3270/93030",
language = "English",
pages = "85--108",
journal = "Comunicazione Politica",
issn = "1594-6061",
publisher = "Societa Editrice IlMulino",

}

RIS

TY - JOUR

T1 - Multi-Party Media Partisanship Attention Score. Estimating Partisan Attention of News Media Sources Using Twitter Data in the Lead-up to 2018 Italian Election

AU - Giglietto, Fabio

AU - Righetti, Nicola

AU - Marino, Giada

AU - Rossi, Luca

PY - 2019/4/1

Y1 - 2019/4/1

N2 - The ongoing radical transformations in communication ecosystems have brought up concerns about the risks of partisan selective exposure and ideological polarization. Traditionally, partisan selective exposure is measured by cross-tabulating survey responses to questions on vote intentions and media consumption. This process is expensive, limits the number of news outlets taken into account and is prone to the typical biases of self-reported data. Building upon previous works and with a specific focus on the online media...

AB - The ongoing radical transformations in communication ecosystems have brought up concerns about the risks of partisan selective exposure and ideological polarization. Traditionally, partisan selective exposure is measured by cross-tabulating survey responses to questions on vote intentions and media consumption. This process is expensive, limits the number of news outlets taken into account and is prone to the typical biases of self-reported data. Building upon previous works and with a specific focus on the online media...

U2 - 10.3270/93030

DO - 10.3270/93030

M3 - Journal article

SP - 85

EP - 108

JO - Comunicazione Politica

JF - Comunicazione Politica

SN - 1594-6061

ER -

ID: 84084971