Falling into the Echo Chamber: the Italian Vaccination Debate on Twitter
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Abstract (arXiv)
The reappearance of measles in the US and Europe, a disease considered eliminated in early 2000s, has been accompanied by a growing debate on the merits of vaccination on social media. In this study we examine the extent to which the vaccination debate on Twitter is conductive to potential outreach to the vaccination hesitant. We focus on Italy, one of the countries most affected by the latest measles outbreaks. We discover that the vaccination skeptics, as well as the advocates, reside in their own distinct "echo chambers". The structure of these communities differs as well, with skeptics arranged in a tightly connected cluster, and advocates organizing themselves around few authoritative hubs. At the center of these echo chambers we find the ardent supporters, for which we build highly accurate network- and content-based classifiers (attaining 95% cross-validated accuracy). Insights of this study provide several avenues for potential future interventions, including network-guided targeting, accounting for the political context, and monitoring of alternative sources of information.
Key facts. Cited by 12 papers in the map (data through 7 Oct 2026). First posted on arXiv 26 Mar 2020.
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Citing papers per year: 2021: 6; 2022: 2; 2023: 2; 2024: 1; 2025: 0; 2026: 1.
12 papers.
- 2021A Survey on Echo Chambers on Social Media: Description, Detection and Mitigationcited by 11
- 2021COVID-19 Vaccine Misinformation Campaigns and Social Media Narrativescited by 7
- 2021Studying Fake News Spreading, Polarisation Dynamics, and Manipulation by Bots: a Tale of Networks and Languagecited by 6
- 2021Learning Ideological Embeddings from Information Cascadescited by 6
- 2022Cascade-based Echo Chamber Detectioncited by 6
- 2021Misleading the Covid-19 vaccination discourse on Twitter: An exploratory study of infodemic around the pandemiccited by 4
- 2023Rebalancing Social Feed to Minimize Polarization and Disagreementcited by 2
- 2021A Machine Learning Pipeline to Examine Political Bias with Congressional Speechescited by 1
- 2023Quantifying the Echo Chamber Effect: An Embedding Distance-based Approachcited by 1
- 2024From Perils to Possibilities: Understanding how Human (and AI) Biases affect Online Foracited by 1
- 2022"Double vaccinated, 5G boosted!": Learning Attitudes towards COVID-19 Vaccination from Social Mediacited by 0
- 2026Revisiting the Objective of Echo Chamber Detectioncited by 0
- 2026Revisiting the Objective of Echo Chamber Detection16 Sep 2026
- 2024From Perils to Possibilities: Understanding how Human (and AI) Biases affect Online Fora21 Mar 2024
- 2023Rebalancing Social Feed to Minimize Polarization and Disagreement28 Aug 2023
- 2023Quantifying the Echo Chamber Effect: An Embedding Distance-based Approach10 Jul 2023
- 2022Cascade-based Echo Chamber Detection9 Aug 2022
- 2022"Double vaccinated, 5G boosted!": Learning Attitudes towards COVID-19 Vaccination from Social Media27 Jun 2022
- 2021A Survey on Echo Chambers on Social Media: Description, Detection and Mitigation9 Dec 2021
- 2021Learning Ideological Embeddings from Information Cascades28 Sep 2021
- 2021A Machine Learning Pipeline to Examine Political Bias with Congressional Speeches18 Sep 2021
- 2021Studying Fake News Spreading, Polarisation Dynamics, and Manipulation by Bots: a Tale of Networks and Language13 Sep 2021
- 2021Misleading the Covid-19 vaccination discourse on Twitter: An exploratory study of infodemic around the pandemic16 Aug 2021
- 2021COVID-19 Vaccine Misinformation Campaigns and Social Media Narratives15 Jun 2021