Publications:
"Does Candidates' Media Exposure Affect Vote Shares? Evidence From Pope Breaking News"
[2023, Journal of Public Economics]
Paper in a nutshell:
The paper addresses the debated question of whether even a very brief exposure to biased media can significantly affect political attitudes.
The study analyzes the effect of a sudden, short-term change in media coverage of politics during the 2013 Italian general election, which coincided with Pope Benedict XVI's unexpected resignation. This caused a temporary but marked reduction in visibility for the TV tycoon Berlusconi, which was sufficient to determine his defeat. In fact, part of his electorate switched to Internet for political news, and later favored a party with online-based propaganda.
This research speaks to the policy debate on media regulation, exposing the limitations of current widespread regulatory approaches (“top-down” attempts to even out politicians’ attention shares within a platform), in a world where voters seek for information across different media types.
Working papers:
"Visual Bias" [Updated draft: Nov 24] (Revise and resubmit, Econometrica)
["Best JM paper award" by Unicredit & EEA, "Marco Fanno" best paper award]
Abstract:
I study the non-verbal language of leading pictures in online news and its influence on readers’ opinions. I develop a visual vocabulary and use a dictionary approach to analyze around 300,000 photos published in US news in 2020. I document that the visual language of US media is politically partisan and significantly polarised, to an extent comparable to the text partisanship in the same news pieces. I then demonstrate experimentally that the news’ partisan visual language is not merely distinctive of outlets’ ideological positions, but also promotes them among readers. In a survey experiment, identical articles with images of opposing partisanships induce different opinions, tilted towards the pictures’ ideological poles. Moreover, as readers react more to images aligned with the ideology of their political affiliation group, the news’ visual bias causes polarization to increase. Finally, I find that media can effectively influence readers by pairing neutral text with partisan images. This highlights the need to incorporate image analysis into news assessments and fact-checking, activities that are currently mainly focusing on text.
Work in progress:
On the political economy of media & AI:
"Algorithmic Social Norms"
On social norms & health:
"Media coverage and norms around prosocial behavior".
"What drives prosocial outcomes? A field experiment on registrations as organ donors".
[on hold] (Awarded the EIEF 2020 Grant)
Project description:
I study the role of cognitive and non-cognitive factors in the take-up of pro-social behaviour, focusing on registrations to posthumously donate organs.