KRİPTO PARA PİYASALARININ KARANLIK YÜZÜ: ENTEGRE BİBLİYOMETRİK BİR ANALİZ

Abstract

Amaç- Bu çalışmanın amacı, kripto para piyasalarının karanlık yönüne ışık tutan yayınları sistematik bir yaklaşımla ortaya koymaktır. Yöntem- Bu amaç doğrultusunda, 2014-2022 tarihleri arasında Scopus veri tabanında yer alan 369 yayın örneklem olarak belirlenmiştir. Veri tabanında yer alan yayınlarda yayın başlığı, özet ve anahtar kelimeler üzerinden “cryptocurrency” ve “fraud”, “scam”, “phishing”, “ponzi”, “crime” kelimeleri taranmış ve entegre bibliyometrik bir analiz yapılmıştır. Analizlerde R programı kullanılmış olup, bulguları görselleştirmek için RStudio programındaki “Biblioshiny” uygulamasından yararlanılmıştır. Bulgular- Elde edilen bulgular, yayın sayısının, atıf sayısının ve alana gösterilen ilginin özellikle son yıllarda arttığını göstermiştir. Alandaki yayın sayısının artış hızı ve bu yayınların çoğunluğunun bildiri aşamasında olması, alanın gelişmekte olan önemli bir alan olduğunu göstermiştir. Alana en yoğun ilgi Çin’de yer alan üniversitelerden gösterilmiştir. Diğer taraftan, alana en fazla ilginin bilgisayar bilimlerinden gösterildiği ve finans alanındaki dergilerin alana ilgisinin zayıf kaldığı görülmüştür. Alanda gelecekte dikkat çekebilecek konuların dijital adli tıp, dijital varlıklar, dolandırıcı kripto para birimleri, yolsuzluk önleme, madencilik ve siber saldırılar olduğu belirlenmiştir. Sonuç- Çalışma, kripto para piyasalarının karanlık yüzünün akademik araştırmalardaki evrimini ortaya koymaktadır. Elde edilen bulgular, alana ilgi duyan araştırmacılara gelecekte gündem olabilecek temaları ve konuları keşfetme olanağı sunmaktadır.

Keywords

• Kripto para
• dolandırıcılık
• suç
• bibliometric analiz

THE DARK SIDE OF CRYPTOCURRENCY MARKETS: AN INTEGRATED BIBLIOMETRIC ANALYSIS

Abstract

Purpose- The aim of this study is to reveal the publications that shed light on the dark side of the cryptocurrency markets with a systematic approach. Methodology- For this purpose, 369 publications in the Scopus database between 2014-2022 were determined as samples. In the publications provided by the database, the keywords "cryptocurrency" and "fraud", "scam", "phishing", "ponzi", "crime" were scanned over the publication title, abstract and keywords, and an integrated bibliometric analysis was employed. The R program was used in the analysis, and the "Biblioshiny" application in the RStudio program was employed to visualize the findings. Findings- The analysis reveals that the number of publications, the number of citations and the interest in the field have increased especially in recent years. The rate of increase in the number of publications in the field and the fact that most of these publications are at the stage of notification have shown that the field is an important developing field. The most intense interest in the field has been shown from universities in China. On the other hand, it was seen that the most interest in the field was from computer sciences and the interest of journals in the field of finance remained weak. It has been determined that the topics that may attract attention in the future are digital forensics, digital assets, fraudulent cryptocurrencies, corruption prevention, mining and cyber attacks. Conclusion- The study reveals the evolution of the dark side of cryptocurrency markets in academic research. The findings provide researchers interested in the field with the opportunity to explore themes and issues that may be on the agenda in the future.

Keywords

• Cryptocurrency
• fraud
• ponzi
• crime
• bibliometric analysis
• Kripto para
• dolandırıcılık
• suç
• bibliometric analiz

References

1. Alsmadi, A., Alrawashdeh, N., Al-Dweik, A & Al-Assaf, M. (2022). Cryptocurrencies: A bibliometric analysis. International Journal of Data and Network Science, 6(3): 619-628.
2. Al-Hashedi, K. G. & Magalingam, P. (2021). Financial fraud detection applying data mining techniques: A comprehensive review from 2009 to 2019. Comput. Sci. Rev., 40 (C). https://doi.org/10.1016/j.cosrev.2021.100402
3. Ante, L. (2021). Smart contracts on the blockchain – A bibliometric analysis and review. Telematics and Informatics, 57 (101519): 1-29.
4. Aysan, A.F., Demirtaş, H.B. & Saraç, M. (2021). The ascent of bitcoin: Bibliometric analysis of bitcoin research. J. Risk Financial Manag., 14 (427). https://doi.org/10.3390/jrfm14090427
5. Bartoletti, M., Carta, S., Cimoli, T. Saia, R. (2019). Dissecting ponzi schemes on ethereum: Identification, analysis, and impact. ArXiv, abs/1703.03779.
6. Biryukov, A. & Tikhomirov, S. (2019). Deanonymization and linkability of cryptocurrency transactions based on network analysis. 2019 IEEE European Symposium on Security and Privacy (EuroS&P), 172-184. doi: 10.1109/EuroSP.2019.00022.
7. Bryans, D. (2014). Bitcoin and money laundering: Mining for an effective solution. 89 Ind. L.J. 441. https://ssrn.com/abstract=2317990
8. Callon, M., Courtial, J. P., & Laville, F. (1991). Co-word analysis as a tool for describing the network of interactions between basic and technological research: The case of polymer chemsitry. Scientometrics, 22(1): 155–205. https://doi.org/10. 1007/BF02019280

9. Chainalysis (2022). The 2022 Crypto Crime Report. https://theblockchaintest.com/uploads/resources/Chainalysys%20-%20Crypto%20Crime%20Report%20-%202022%20Feb.pdf (01.11.2022).
10. Chen, W., Zheng, Z., Cui, J., Ngaı, E., Zheng, P. & Zhou, Y. (2018). Detecting ponzi schemes on ethereum: Towards healthier blockchain technology. In WWW 2018: The 2018 Web Conference. April23–27, 2018, Lyon, France, ACM, New York, NY, USA, Article 4: 1409-1418.
11. Conti, M., Gangwal, A., & Ruj, S. (2018). On the economic significance of ransomware campaigns: A Bitcoin transactions perspective. Comput. Secur., 79: 162-189.
12. Çizmecioğlu, S. & Akman, A. Z. (2021). Blok zincir ve kripto para konularının bibliyometrik bir analizi: 2015-2020 dönemi. Business Economics and Management Research Journal , 4 (1) , 1-16 . Retrieved from https://dergipark.org.tr/tr/pub/bemarej/issue/62931/931012
13. Di Battista, G., Di Donato, V., Patrignani, M., Pizzonia, M., Roselli, V. & Tamassia, R. (2015). Bitconeview: Visualization of flows in the bitcoin transaction graph. 2015 IEEE Symposium on Visualization for Cyber Security (VizSec), 1-8. doi: 10.1109/VIZSEC.2015.7312773.
14. Gandal, N., Hamrick, JT., Moore, T. & Oberman, T. (2018). Price manipulation in the Bitcoin ecosystem. Journal of Monetary Economics, Elsevier, 95(C): 86-96.
15. Gao, Y.L., Chen, X. B., Chen, L. Y., Sun, Y., Niu, X. X. & Yang, Y. X. (2018). A secure cryptocurrency scheme based on post-quantum blockchain. IEEE Access, 6: 27205-27213. doi: 10.1109/ACCESS.2018.2827203.
16. García-Corral, F. J., Cordero-García, J. A., de Pablo-Valenciano, J., & Uribe-Toril, J. (2022). A bibliometric review of cryptocurrencies: how have they grown?. Financial Innovation, 8(1): 1-31. https://doi.org/10.1186/s40854-021-00306-5
17. Guo, X. & Donev, P. (2020). Bibliometrics and network analysis of cryptocurrency research. J Syst Sci Complex, 33: 1933–1958.
18. Jalal, R. N. U. D., Alon, I., & Paltrinieri, A. (2021). A bibliometric review of cryptocurrencies as a financial asset. Technology Analysis & Strategic Management, 1-16. https://doi.org/10.1080/09537325.2021.1939001
19. Jeris, S.S., Ur Rahman Chowdhury, A.S.M.N., Akter, M.T., Frances, S. & Roy M.H. (2022). Cryptocurrency and stock market: bibliometric and content analysis. Heliyon, 8(9): e10514. doi: 10.1016/j.heliyon.2022.e10514. PMID: 36105470; PMCID: PMC9465106.
20. Kamps, J. & Kleinberg, B. (2018). To the moon: defining and detecting cryptocurrency pump-and-dumps. Crime Sci, 7(18).
21. Kethineni, S., & Cao, Y. (2020). The Rise in Popularity of Cryptocurrency and Associated Criminal Activity. International Criminal Justice Review, 30(3): 325–344. https://doi.org/10.1177/1057567719827051
22. Lotka, A. J. (1926). The frequency distribution of scientific productivity. Journal of the Washington Academy of Sciences, 16(12), 317-323.
23. Monamo, P., Marivate, V. & Twala, B. (2016). Unsupervised learning for robust Bitcoin fraud detection. Information Security for South Africa (ISSA), 129-134. doi: 10.1109/ISSA.2016.7802939.
24. Nakamoto S. (2008). Bitcoin: A peer-to-peer electronic cash system.
25. Nasir, A., Shaukat, K., Hameed , Ibrahim A., Luo S., Alam T. M. & Iqbal F. (2020). A bibliometric analysis of corona pandemic in social sciences: A review of influential aspects and conceptual structure. IEEE Access, 8: 133377-133402. DOI: 10.1109/ACCESS.2020.3008733
26. Nasir, A., Shaukat, K., Khan, K. I., Hameed, I. A., Alam, T. M., & Luo, S. (2021). What is core and what future holds for blockchain technologies and cryptocurrencies: A bibliometric analysis. IEEE Access, 9: 989-1004. https://doi.org/10.1109/ACCESS.2020.3046931
27. Sousa, A., Calçada, E., Rodrigues, P. & Pinto Borges, A. (2022), Cryptocurrency adoption: A systematic literature review and bibliometric analysis. EuroMed Journal of Business, 17(3), 374-390. https://doi.org/10.1108/EMJB-01-2022-0003
28. Sun Yin, H. & Vatrapu, R. (2017). A first estimation of the proportion of cybercriminal entities in the bitcoin ecosystem using supervised machine learning. IEEE International Conference on Big Data (Big Data), 3690-3699. doi: 10.1109/BigData.2017.8258365.
29. Trozze, A., Kamps, J., Akartuna, E.A. et al. /2022). Cryptocurrencies and future financial crime. Crime Sci 11, 1. https://doi.org/10.1186/s40163-021-00163-8
30. Yavuz, E., Koç, A. K., Çabuk, U. C. & Dalkılıç, G. (2018). Towards secure e-voting using ethereum blockchain. 6th International Symposium on Digital Forensic and Security (ISDFS), 1-7. doi: 10.1109/ISDFS.2018.8355340.