ArticleRoyal Society open science2022
The voice of few, the opinions of many: evidence of social biases in Twitter COVID-19 fake news sharing.
Article in Royal Society open science, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
11 citing papers in PubMed.
- Longitudinal predictors of vaccine conspiracy beliefs: findings from a five-wave panel study in Japan.Scientific reports · 2026Article
- #WhatIEatinaDay: The Quality, Accuracy, and Engagement of Nutrition Content on TikTok.Nutrients · 2025Article
- Article
- Article
- Modelling and predicting online vaccination views using bow-tie decomposition.Royal Society open science · 2024Article
- A Novel Approach for the Early Detection of Medical Resource Demand Surges During Health Care Emergencies: Infodemiology Study of Tweets.JMIR formative research · 2024Article
- Article
- The intrinsic and extrinsic factors predicting fake news sharing among social media users: the moderating role of fake news awareness.Current psychology (New Brunswick, N.J.) · 2023Article
- The voice of few, the opinions of many: evidence of social biases in Twitter COVID-19 fake news sharing.Royal Society open science · 2022Article
- Emotional profiling and cognitive networks unravel how mainstream and alternative press framed AstraZeneca, Pfizer and COVID-19 vaccination campaigns.Scientific reports · 2022Article
- Bow-tie structures of twitter discursive communities.Scientific reports · 2022Article
Corrections and comments
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Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Online platforms play a relevant role in the creation and diffusion of false or misleading news. Concerningly, the COVID-19 pandemic is shaping a communication network which reflects the emergence of collective attention towards a topic that rapidly gained universal interest. Here, we characterize the dynamics of this network on Twitter, analysing how unreliable content distributes among its users. We find that a minority of accounts is responsible for the majority of the misinformation circulating online, and identify two categories of users: a few active ones, playing the role of 'creators', and a majority playing the role of 'consumers'. The relative proportion of these groups (approx. 14% creators-86% consumers) appears stable over time: consumers are mostly exposed to the opinions of a vocal minority of creators (which are the origin of 82% of fake content in our data), that could be mistakenly understood as representative of the majority of users. The corresponding pressure from a perceived majority is identified as a potential driver of the ongoing COVID-19 infodemic.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.