Ponzi Schemes in relation to Cryptocurrency
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Ponzi Schemes in relation to Cryptocurrency
1.
What articles have similarities in each section below?
a.
Methodology
There was a similarity in the methodology that Galletta & Pinelli (2023) and He et al. (2022) used. Galletta & Pinelli (2023) utilized experimental evaluation to classify different forms of fraud. Likewise, He et al. (2022) performed experiments to explore cryptocurrency fraud.
b.
Findings
Across the board, the studies indicated that fraud in relation to cryptocurrency has been on the rise. The literature review by Trozze et al. (2022) found several classifications of fraud associated with cryptocurrency. Their research showed that Ponzi schemes were the most common form of fraud. Galletta and Pinelli (2023) also showed that there is a high number of Ponzi investments nowadays. Phan et al. (2019) showed that most conversations across social media reflected the frequency in the existence of cryptocurrency scams. Similarly, the experiments by Phan et al. (2019) also revealed the existence of a significant number of Ponzi contracts. Generally, the studies depicted that Ponzi schemes have become very frequent in crypto.
c.
Recommendations
Trozze et al. (2022) recommended that there is a need for more research on the subject and the determination of effective measures for mitigation. On the same note, Phan et al. (2019) stated that further research is necessary to expand the understanding of crypto scams and ways to prevent them. He et al. (2022) also recommended the need for further studies to enable the detection and prevention of Ponzi schemes.
2.
What articles have differences in each section below?
a.
Methodology
Whereas He et al. (2022) and Galletta & Pinelli (2023) used experimental methodology, Phan et al. (2019) used observation, while Trozze et al. (2022) conducted their study through the use of systematic review. In addition, Galletta & Pinelli (2023) and He et al. (2022) relied on open-source, whereas Phan et al. (2019) used social media (Twitter) and Trozze et al. (2022) used publication databases.
b.
Findings
While the findings from all studies pointed to the rise in crypto scams, they featured variations in their focus points. While Trozze et al. (2022) focused on classifying the frequency of different forms of crypto fraud, including Ponzi schemes, pump-and-dump schemes, and market manipulation, Galletta and Pinelli (2023) and He et al. (2022) on the other hand only focused on Ponzi schemes and smart Ponzi contracts associated with Ethereum. The study by Phan et al. (2019) was also different from the other research in that their findings featured coverage of scams and fraud in general. Their research observed the entirety of conversations associated with cryptocurrency, scams, and fraud.
c.
Recommendations
The recommendations by He et al. (2022), Phan et al. (2019), and Trozze et al. (2022) mainly revolved around conducting more research to aid the understanding or detection, and prevention of crypto fraud. In contrast, Galletta & Pinelli (2023) looked at further developing a model for classifying and detecting different forms of cryptocurrency fraud.
References
Galletta, L., & Pinelli, F. (2023). Sharpening Ponzi Schemes Detection on Ethereum with Machine Learning.
arXiv preprint arXiv:2301.04872. https://arxiv.org/pdf/2301.04872.pdf
He, X., Yang, T., & Chen, L. (2022). CTRF: Ethereum-Based Ponzi Contract Identification.
Security and Communication Networks,
2022. https://doi.org/10.1155/2022/1554752
Phan, L., Li, S., & Mentzer, K. (2019). Blockchain technology and the current discussion on fraud.
Information Systems and Analytics Journal Articles. https://digitalcommons.bryant.edu/cgi/viewcontent.cgi?article=1027&context=cisjou\
Trozze, A., Kamps, J., Akartuna, E. A., Hetzel, F. J., Kleinberg, B., Davies, T., & Johnson, S. D. (2022). Cryptocurrencies and future financial crime.
Crime Science,
11, 1-35. 10.1186/s40163-021-00163-8
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