IDEAS home Printed from https://ideas.repec.org/r/nat/natcom/v10y2019i1d10.1038_s41467-018-07761-2.html
   My bibliography  Save this item

Influence of fake news in Twitter during the 2016 US presidential election

Citations

Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
as


Cited by:

  1. Ho-Chun Herbert Chang & Emilio Ferrara, 2022. "Comparative analysis of social bots and humans during the COVID-19 pandemic," Journal of Computational Social Science, Springer, vol. 5(2), pages 1409-1425, November.
  2. Kai-Cheng Yang & Emilio Ferrara & Filippo Menczer, 2022. "Botometer 101: social bot practicum for computational social scientists," Journal of Computational Social Science, Springer, vol. 5(2), pages 1511-1528, November.
  3. Mao, Yajun & Rong, Zhihai & Wu, Zhi-Xi, 2021. "Effect of collective influence on the evolution of cooperation in evolutionary prisoner’s dilemma games," Applied Mathematics and Computation, Elsevier, vol. 392(C).
  4. Marius Dragomir & José Rúas-Araújo & Minna Horowitz, 2024. "Beyond online disinformation: assessing national information resilience in four European countries," Palgrave Communications, Palgrave Macmillan, vol. 11(1), pages 1-10, December.
  5. Sven Gruener, 2024. "Determinants of Gullibility to Misinformation: A Study of Climate Change, COVID-19 and Artificial Intelligence," Journal of Interdisciplinary Economics, , vol. 36(1), pages 58-78, January.
  6. So-Min Cheong & Matthew Babcock, 2021. "Attention to misleading and contentious tweets in the case of Hurricane Harvey," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 105(3), pages 2883-2906, February.
  7. Yongjun Zhang & Hao Lin & Yi Wang & Xinguang Fan, 2023. "Sinophobia was popular in Chinese language communities on Twitter during the early COVID-19 pandemic," Palgrave Communications, Palgrave Macmillan, vol. 10(1), pages 1-12, December.
  8. Ciprian-Octavian Truică & Elena-Simona Apostol, 2022. "MisRoBÆRTa: Transformers versus Misinformation," Mathematics, MDPI, vol. 10(4), pages 1-25, February.
  9. Peter D. Lunn & Cameron A. Belton & Ciarán Lavin & Féidhlim P. McGowan & Shane Timmons & Deirdre A. Robertson, 2020. "Using behavioral science to help fight the Coronavirus," Journal of Behavioral Public Administration, Center for Experimental and Behavioral Public Administration, vol. 3(1).
  10. Jairo León-Quismondo, 2023. "Social Sensing and Individual Brands in Sports: Lessons Learned from English-Language Reactions on Twitter to Pau Gasol’s Retirement Announcement," IJERPH, MDPI, vol. 20(2), pages 1-13, January.
  11. Raj, Chahat & Meel, Priyanka, 2022. "People lie, actions Don't! Modeling infodemic proliferation predictors among social media users," Technology in Society, Elsevier, vol. 68(C).
  12. Carlos Carrasco-Farré, 2022. "The fingerprints of misinformation: how deceptive content differs from reliable sources in terms of cognitive effort and appeal to emotions," Palgrave Communications, Palgrave Macmillan, vol. 9(1), pages 1-18, December.
  13. Uğur Baloğlu, 2021. "Trolls, Pressure and Agenda: The discursive fight on Twitter in Turkey," Media and Communication, Cogitatio Press, vol. 9(4), pages 39-51.
  14. Lisa Singh & Leticia Bode & Ceren Budak & Kornraphop Kawintiranon & Colton Padden & Emily Vraga, 2020. "Understanding high- and low-quality URL Sharing on COVID-19 Twitter streams," Journal of Computational Social Science, Springer, vol. 3(2), pages 343-366, November.
  15. Hyehyun Hong & Hyun Jee Oh, 2020. "Utilizing Bots for Sustainable News Business: Understanding Users’ Perspectives of News Bots in the Age of Social Media," Sustainability, MDPI, vol. 12(16), pages 1-16, August.
  16. Tiago A. Schieber & Laura C. Carpi & Panos M. Pardalos & Cristina Masoller & Albert Díaz-Guilera & Martín G. Ravetti, 2023. "Diffusion capacity of single and interconnected networks," Nature Communications, Nature, vol. 14(1), pages 1-9, December.
  17. James Flamino & Alessandro Galeazzi & Stuart Feldman & Michael W. Macy & Brendan Cross & Zhenkun Zhou & Matteo Serafino & Alexandre Bovet & Hernán A. Makse & Boleslaw K. Szymanski, 2023. "Political polarization of news media and influencers on Twitter in the 2016 and 2020 US presidential elections," Nature Human Behaviour, Nature, vol. 7(6), pages 904-916, June.
  18. Jeremy Straub & Matthew Spradling & Bob Fedor, 2022. "Assessment of Factors Impacting the Perception of Online Content Trustworthiness by Age, Education and Gender," Societies, MDPI, vol. 12(2), pages 1-66, March.
  19. Wang, Yan & Li, Haozhan & Zhang, Ling & Zhao, Linlin & Li, Wanlan, 2022. "Identifying influential nodes in social networks: Centripetal centrality and seed exclusion approach," Chaos, Solitons & Fractals, Elsevier, vol. 162(C).
  20. Mujtaba Ali Isani, 2021. "Methodological Problems of Using Arabic-Language Twitter as a Gauge for Arab Attitudes Toward Politics and Society," Contemporary Review of the Middle East, , vol. 8(1), pages 22-35, March.
  21. Noha Alnazzawi & Najlaa Alsaedi & Fahad Alharbi & Najla Alaswad, 2022. "Using Social Media to Detect Fake News Information Related to Product Marketing: The FakeAds Corpus," Data, MDPI, vol. 7(4), pages 1-13, April.
  22. Ciprian-Octavian Truică & Elena-Simona Apostol, 2023. "It’s All in the Embedding! Fake News Detection Using Document Embeddings," Mathematics, MDPI, vol. 11(3), pages 1-29, January.
  23. Junhui Cai & Dan Yang & Wu Zhu & Haipeng Shen & Linda Zhao, 2021. "Network regression and supervised centrality estimation," Papers 2111.12921, arXiv.org.
  24. Kathie M. d'I. Treen & Hywel T. P. Williams & Saffron J. O'Neill, 2020. "Online misinformation about climate change," Wiley Interdisciplinary Reviews: Climate Change, John Wiley & Sons, vol. 11(5), September.
  25. Matthew Spradling & Jeremy Straub, 2022. "Evaluation of the Factors That Impact the Perception of Online Content Trustworthiness by Income, Political Affiliation and Online Usage Time," Future Internet, MDPI, vol. 14(11), pages 1-55, November.
  26. Lodh, Rishab & Dey, Oindrila, 2023. "“Fake news alert!”: A game of misinformation and news consumption behavior," MPRA Paper 118371, University Library of Munich, Germany.
  27. Xu, Shuqi & Mariani, Manuel Sebastian & Lü, Linyuan & Medo, Matúš, 2020. "Unbiased evaluation of ranking metrics reveals consistent performance in science and technology citation data," Journal of Informetrics, Elsevier, vol. 14(1).
  28. Gruener, Sven, 2021. "Susceptibility to misinformation: a study of climate change, Covid-19, and artificial intelligence," SocArXiv x8efq, Center for Open Science.
  29. Yevgeniy Golovchenko, 2020. "Measuring the scope of pro-Kremlin disinformation on Twitter," Palgrave Communications, Palgrave Macmillan, vol. 7(1), pages 1-11, December.
  30. Nwaibeh, E.A. & Chikwendu, C.R., 2023. "A deterministic model of the spread of scam rumor and its numerical simulations," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 207(C), pages 111-129.
  31. Quintino Francesco Lotito & Davide Zanella & Paolo Casari, 2021. "Realistic Aspects of Simulation Models for Fake News Epidemics over Social Networks," Future Internet, MDPI, vol. 13(3), pages 1-20, March.
  32. Ye, Yucheng & Xu, Shuqi & Mariani, Manuel Sebastian & Lü, Linyuan, 2022. "Forecasting countries' gross domestic product from patent data," Chaos, Solitons & Fractals, Elsevier, vol. 160(C).
  33. John Bryden & Eric Silverman, 2019. "Underlying socio-political processes behind the 2016 US election," PLOS ONE, Public Library of Science, vol. 14(4), pages 1-11, April.
  34. Nirmalya Thakur & Kesha A. Patel & Audrey Poon & Rishika Shah & Nazif Azizi & Changhee Han, 2023. "A Comprehensive Analysis and Investigation of the Public Discourse on Twitter about Exoskeletons from 2017 to 2023," Future Internet, MDPI, vol. 15(10), pages 1-46, October.
  35. Hou, Lei, 2022. "Network versus content: The effectiveness in identifying opinion leaders in an online social network with empirical evaluation," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 592(C).
  36. Chuhan Wu & Fangzhao Wu & Tao Qi & Wei-Qiang Zhang & Xing Xie & Yongfeng Huang, 2022. "Removing AI’s sentiment manipulation of personalized news delivery," Palgrave Communications, Palgrave Macmillan, vol. 9(1), pages 1-9, December.
  37. Lipić, Tomislav & Štajduhar, Andrija & Medvidović, Luka & Wild, Dorian & Korošak, Dean & Podobnik, Boris, 2022. "Stringency without efficiency is not adequate to combat pandemics," Chaos, Solitons & Fractals, Elsevier, vol. 160(C).
IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.