Understanding and countering the spread of conspiracy theories in social networks: Evidence from epidemiological models of Twitter data
出版年份 2021 全文链接
标题
Understanding and countering the spread of conspiracy theories in social networks: Evidence from epidemiological models of Twitter data
作者
关键词
Twitter, Social networks, Social theory, Epidemiology, COVID 19, Social media, Social epidemiology, SARS CoV 2
出版物
PLoS One
Volume 16, Issue 8, Pages e0256179
出版商
Public Library of Science (PLoS)
发表日期
2021-08-13
DOI
10.1371/journal.pone.0256179
参考文献
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注意:仅列出部分参考文献,下载原文获取全部文献信息。- The echo chamber effect on social media
- (2021) Matteo Cinelli et al. PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA
- How to fight an infodemic
- (2020) John Zarocostas LANCET
- COVID-19 and the 5G Conspiracy Theory: Social Network Analysis of Twitter Data
- (2020) Wasim Ahmed et al. JOURNAL OF MEDICAL INTERNET RESEARCH
- FakeNewsNet: A Data Repository with News Content, Social Context, and Spatiotemporal Information for Studying Fake News on Social Media
- (2020) Kai Shu et al. Big Data
- The COVID-19 social media infodemic
- (2020) Matteo Cinelli et al. Scientific Reports
- EpiModel: An R Package for Mathematical Modeling of Infectious Disease over Networks
- (2018) Samuel M. Jenness et al. Journal of Statistical Software
- The spread of true and false news online
- (2018) Soroush Vosoughi et al. SCIENCE
- Echo chambers and viral misinformation: Modeling fake news as complex contagion
- (2018) Petter Törnberg PLoS One
- Combating Information Attacks in the Age of the Internet: New Challenges for Cognitive Engineering
- (2018) Mica R. Endsley HUMAN FACTORS
- Influence of fake news in Twitter during the 2016 US presidential election
- (2018) Alexandre Bovet et al. Nature Communications
- Modeling the infectiousness of Twitter hashtags
- (2017) Jonathan Skaza et al. PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS
- Like It or Not
- (2016) Anastasia Giachanou et al. ACM COMPUTING SURVEYS
- Avoidable errors in the modelling of outbreaks of emerging pathogens, with special reference to Ebola
- (2015) A. A. King et al. PROCEEDINGS OF THE ROYAL SOCIETY B-BIOLOGICAL SCIENCES
- Risk Communication and Crisis Communication in Infectious Disease Outbreaks in Germany: What Is Being Done, and What Needs to be Done
- (2014) Petra Dickmann et al. Disaster Medicine and Public Health Preparedness
- Detecting misinformation in online social networks using cognitive psychology
- (2014) K P Krishna Kumar et al. Human-centric Computing and Information Sciences
- An epidemic model of rumor diffusion in online social networks
- (2013) Jun-Jun Cheng et al. EUROPEAN PHYSICAL JOURNAL B
- The dynamics of audience applause
- (2013) R. P. Mann et al. Journal of the Royal Society Interface
- SIR rumor spreading model in the new media age
- (2012) Laijun Zhao et al. PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS
- Rumors in a Network: Who's the Culprit?
- (2011) Devavrat Shah et al. IEEE TRANSACTIONS ON INFORMATION THEORY
- SIHR rumor spreading model in social networks
- (2011) Laijun Zhao et al. PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS
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