Abstract
This paper presents a new social media phenomenon that sees users lying about their deceptive motivations by either dishonestly claiming that they are not bots or by asserting that real news is actually fake news. We analyzed the use of the #FakeNews and #NotABot hashtags in Twitter data collected on the 2019 Canadian federal elections. Our findings show that the #FakeNews hashtag was most likely to be connected to an established news source rather than an actual fake news site and that users of the #NotABot hashtag were no more likely to be human than other users in our data set. This phenomenon of lying about lying has been used to discredit well-known news organizations and amplify political misinformation, showing how online influence campaigns continue to evolve to manipulate social media users even as people have become more aware of the dangers of online misinformation.
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Acknowledgement
This work was supported in part by the Knight Foundation and Office of Naval Research Award 00014182106. Additional support was provided by the Center for Computational Analysis of Social and Organizational Systems (CASOS) and the Center for Informed Democracy and Social Cybersecurity (IDeaS). The views and conclusions contained in this document are those of the authors and should not be interpreted as representing the official policies, either expressed or implied, of the Knight Foundation, the Office of Naval Research, or the U.S. government. The authors would also like to thank David Beskow for collecting the data used in this study and for running his BotHunter algorithm on the data. We would also like to thank Binxuan Huang for access to his Twitter user identity classification system.
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This paper is an extension of the conference paper, “Lying about Lying: A Case Study of the 2019 Canadian Elections” King et al. (2020).
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Bellutta, D., King, C. & Carley, K.M. Deceptive accusations and concealed identities as misinformation campaign strategies. Comput Math Organ Theory 27, 302–323 (2021). https://doi.org/10.1007/s10588-021-09328-x
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DOI: https://doi.org/10.1007/s10588-021-09328-x