Page 81 - False Information

https://doi.org/10.1016/j.tele.2020.101475

Apuke, O. D., & Omar, B. (2020b). Fake news and COVID-19:
modelling the predictors of fake news sharing among social
media users. Telematics and Informatics, 101475.
https://doi.org/10.1016/j.tele.2020.101475
Apuke, O. D., & Omar, B. (2020c). Fake news proliferation in
Nigeria: Consequences, motivations, and prevention
through awareness strategies. Humanities and Social
Sciences Reviews. https://doi.org/10.18510/hssr.2020.8236
Arif, A., Robinson, J. J., Stanek, S. A., Fichet, E., Townsend, P.,
Worku, Z., & Starbird, K. (2017). A closer look at the self-
correcting crowd: Examining corrections in online rumors.
Proceedings of the ACM Conference on Computer
Supported Cooperative Work, CSCW.
https://doi.org/10.1145/2998181.2998294
Babcock, M., Cox, R. A. V., & Kumar, S. (2019). Diffusion of pro-
and anti-false information tweets: the Black Panther movie
case. Computational and Mathematical Organization
Theory. https://doi.org/10.1007/s10588-018-09286-x

Baek, Y. M., Kang, H., & Kim, S. (2019). Fake News Should Be
Regulated Because It Influences Both ―Others‖ and ―Me‖:
How and Why the Influence of Presumed Influence Model
Should Be Extended. Mass Communication and Society,
22(3), 301–323.
https://doi.org/10.1080/15205436.2018.1562076
Bakdash, J. Z., Hutchinson, S., Zaroukian, E. G., Marusich, L. R.,
Thirumuruganathan, S., Sample, C., Hoffman, B., & Das,
G. (2018). Malware in the future? Forecasting of analyst
detection of cyber events. Journal of Cybersecurity, 4(1), 1–
10. https://doi.org/10.1093/cybsec/tyy007
Barbieri, F., Ronzano, F., & Saggion, H. (2015). Do we criticise
(and Laugh) in the same way? Automatic detection of

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