Cross Reference Down
Bhosale, S and Di Troia, F (2022). Twitter Bots’ Detection with Benford’s Law and Machine Learning. In Proceedings of Silicon Valley Cybersecurity Conference. SVCC 2022. Communications in Computer and Information Science, vol 1683, Bathen, L., Saldamli, G., Sun, X., Austin, T.H., Nelson, A.J. (eds). Springer, Cham.
This work cites the following items of the Benford Online Bibliography:
| Benford, F (1938). The law of anomalous numbers. Proceedings of the American Philosophical Society, Vol. 78, No. 4 (Mar. 31, 1938), pp. 551-572. |  |
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| Golbeck, J (2015). Benford’s Law Applies to Online Social Networks. PLoS ONE 10(8): e0135169. DOI:10.1371/journal.pone.0135169. | |
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| Golbeck, J (2019). Benford’s Law can detect malicious social bots. First Monday 24(8). DOI:10.5210/fm.v24i8.10163. | |
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| Madahali, L and Hall, M (2020). Application of the Benford’s law to Social bots and Information Operations activities. International Conference on Cyber Situational Awareness, Data Analytics and Assessment (CyberSA), Dublin, Ireland, pp. 1-8. DOI:10.1109/CyberSA49311.2020.9139709. | |
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| Mbona, I and Eloff, JHP (2022). Feature selection using Benford’s law to support detection of malicious social media bots. Information Sciences 582, pp. 369-381. DOI:10.1016/j.ins.2021.09.038. | |
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| Newcomb, S (1881). Note on the frequency of use of the different digits in natural numbers. American Journal of Mathematics 4(1), pp. 39-40. ISSN/ISBN:0002-9327. DOI:10.2307/2369148. | |
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