Psycholinguistic Markers of COVID-19 Conspiracy Tweets and Predictors of Tweet Dissemination-Reference-Cited by-同舟云学术

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Psycholinguistic Markers of COVID-19 Conspiracy Tweets and Predictors of Tweet Dissemination

Published:2021-05-20 Issue: Volume: Page:1-10
ISSN:1041-0236
Container-title:Health Communication
language:en
Short-container-title:Health Communication

Author:

Rains Stephen A.¹,Leroy Gondy²,Warner Echo L.³,Harber Philip⁴

Affiliation:

1. Department of Communication, University of Arizona

2. Eller College of Management, University of Arizona

3. Arizona Cancer Center and College of Nursing, University of Arizona

4. Department of Community, Environment, and Policy, Mel and Enid Zuckerman College of Public Health, University of Arizona

Funder

Eller College of Management at the University of Arizona

Publisher

Informa UK Limited

Subject

Communication,Health(social science)

Link

https://www.tandfonline.com/doi/pdf/10.1080/10410236.2021.1929691

Reference33 articles.

1. COVID-19 and the 5G Conspiracy Theory: Social Network Analysis of Twitter Data

2. Health-protective behaviour, social media usage and conspiracy belief during the COVID-19 public health emergency

3. Cultural carrying capacity: Organ donation advocacy, discursive framing, and social media engagement

4. Inducing Resistance to Conspiracy Theory Propaganda: Testing Inoculation and Metainoculation Strategies

5. Belief in COVID‐19 Conspiracy Theories Reduces Social Distancing over Time

Cited by 12 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Global Perspective on EMR and eHealth;International Journal of Intelligent Information Technologies;2024-07-16

2. Twitter users perceptions of AI-based e-learning technologies;Scientific Reports;2024-03-11

3. The anatomy of conspiracy theorists: Unveiling traits using a comprehensive Twitter dataset;Computer Communications;2024-03

4. Mechanisms Driving Online Vaccine Debate During the COVID-19 Pandemic;Social Media + Society;2024-01

5. Detecting nuance in conspiracy discourse: Advancing methods in infodemiology and communication science with machine learning and qualitative content coding;PLOS ONE;2023-12-20

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