Transaction Types in Cryptocurrencies

The cryptocurrency ecosystem has witnessed an explosive growth, and this study delves into the mechanisms that fuel this expansion. Focusing on airdrops, staking, farming, and coin burning, the research analyzes a vast dataset of transactions from the Ethereum and Binance Networks. This analysis sheds light on the strategic use of these tools by highlighting transactions that engage users and distribute rewards (e.g., airdrops, staking). Furthermore, the study investigates farming as a method to enhance market efficiency by providing liquidity, and coin burning as a strategy to manage token supply and potentially increase value through scarcity. While effective utilization of these mechanisms can bolster token value and project success, regulatory challenges remain. Ultimately, this study aims to raise public awareness of cryptocurrency transaction types and the associated risks. Although many researchers have studied illicit flows on cryptocurrency transactions, in literature we haven’t confronted with any study regarding transaction types. By analyzing over 107 million transaction records, the research presents the distribution of these transaction types. With the analysis of the transaction types, the definitions of them, the statistical outputs from the more than 107 million transaction records from ERC20 and BEP20 blockchain systems and the analysis of some specific token types such as Pancake Swap and Shiba, this research is the first study to present an academic approach with statistical analysis. This study can provide investors with knowledge that safeguard them from the potential pitfalls of cryptocurrency transactions. Also, this study presents some basic statistics so as to understand main patterns of different types of transactions.

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Publication Details

Published
2024-09-21
DOI
https://doi.org/10.1109/idap64064.2024.10711051
Primary Topic
advanced mathematical theories
Type
article
Field-Weighted Citation Impact
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article

Transaction Types in Cryptocurrencies

Taha Uysal, Hüseyin Ünözkan
advanced mathematical theories
article

Transaction Types in Cryptocurrencies

Taha Uysal, Hüseyin Ünözkan
article en

Abstract

The cryptocurrency ecosystem has witnessed an explosive growth, and this study delves into the mechanisms that fuel this expansion. Focusing on airdrops, staking, farming, and coin burning, the research analyzes a vast dataset of transactions from the Ethereum and Binance Networks. This analysis sheds light on the strategic use of these tools by highlighting transactions that engage users and distribute rewards (e.g., airdrops, staking). Furthermore, the study investigates farming as a method to enhance market efficiency by providing liquidity, and coin burning as a strategy to manage token supply and potentially increase value through scarcity. While effective utilization of these mechanisms can bolster token value and project success, regulatory challenges remain. Ultimately, this study aims to raise public awareness of cryptocurrency transaction types and the associated risks. Although many researchers have studied illicit flows on cryptocurrency transactions, in literature we haven’t confronted with any study regarding transaction types. By analyzing over 107 million transaction records, the research presents the distribution of these transaction types. With the analysis of the transaction types, the definitions of them, the statistical outputs from the more than 107 million transaction records from ERC20 and BEP20 blockchain systems and the analysis of some specific token types such as Pancake Swap and Shiba, this research is the first study to present an academic approach with statistical analysis. This study can provide investors with knowledge that safeguard them from the potential pitfalls of cryptocurrency transactions. Also, this study presents some basic statistics so as to understand main patterns of different types of transactions.

Vol. 4
Haliç University (TR), Fenerbahçe University (TR)
Openalex Percentile: Top 70%
advanced mathematical theories
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