The Anatomy of a Cryptocurrency Pump-and-Dump Scheme

Xu, Jiahua; Livshits, Benjamin

doi:10.48550/arxiv.1811.10109

Cited by 3 publications

(2 citation statements)

References 16 publications

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“…The work that is most related to ours is [33], where the main goal is predicting which coin will be pumped based on social signals from Telegram. The authors focus on "pre-pump" messages that announce an upcoming pump operation, but do not mention a coin.…”

Section: Related Workmentioning

confidence: 99%

Identifying and Analyzing Cryptocurrency Manipulations in Social Media

Mirtaheri

Abu-El-Haija²,

Steeg³

et al. 2019

Preprint

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Interest surrounding cryptocurrencies, digital or virtual currencies that are used as a medium for financial transactions, has grown tremendously in recent years. The anonymity surrounding these currencies makes investors particularly susceptible to fraud-such as "pump and dump" scams-where the goal is to artificially inflate the perceived worth of a currency, luring victims into investing before the scammers can sell their holdings. Because of the speed and relative anonymity offered by social platforms such as Twitter and Telegram, social media has become a preferred platform for scammers who wish to spread false hype about the cryptocurrency they are trying to pump. In this work we propose and evaluate a computational approach that can automatically identify pump and dump scams as they unfold by combining information across social media platforms. We also develop a multi-modal approach for predicting whether a particular pump attempt will succeed or not. Finally, we analyze the prevalence of bots in cryptocurrency related tweets, and observe a significant significant presence of bots during the pump attempts. KEYWORDScryptocurrency, pump and dump, social media data mining, anomaly detection

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Section: Related Workmentioning

confidence: 99%

Identifying and Analyzing Cryptocurrency Manipulations in Social Media

Mirtaheri

Abu-El-Haija²,

Steeg³

et al. 2019

Preprint

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“…Blockchain-base games exist in the environment of ubiquitous speculation that is characteristic for cryptocurrency markets [19] [20]. Upon closer look, NFT markets demonstrate the same type of player behavior, asset 'flipping' being the most common practice [21].…”

Section: Introductionmentioning

confidence: 99%

Vintage CryptoKitties and the Quest for Authenticity

Serada

2021

2021 IEEE Conference on Games (CoG)

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This paper presents the case of the blockchain-based game Cryp-toKitties (Axiom Zen, 2017), more specifically, one particular way of making game tokens potentially more valuable by labeling them 'vintage'. Firstly, I show how the meaning of 'vintage' was collectively constructed by the community of players and negotiated online until it was acknowledged by the owners of the game. Secondly, I measure the influence of the 'vintage' label on the game market in the first six months of 2018. I base my measurements on open market data available through such services as KittyHelper, Etherscan and the Chrome plug-in CKBox. I conclude that 'vintage kitties' did not acquire surplus market value even after they became a publicly recognized part of the game: breeding them resulted in losses for the majority of players. However, their retro aesthetics inspired creativity of many players and signified the social status of "the new rich".

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Community Impact on a Cryptocurrency: Twitter Comparison Example Between Dogecoin and Litecoin

Lansiaux¹,

Tchagaspanian²,

Forget

2022

Front. Blockchain

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Context: The third generation of cryptocurrencies gathers cryptocurrencies that are as diverse as the market is big (e.g., Dogecoin or Litecoin). While Dogecoin is seen as a memecoin, the other gathers a very different category of investors. To our knowledge, no study has independently assessed the crypto community’s economical impact on these cryptocurrencies. Furthermore, various methodological possibilities exist to forecast cryptocurrency price—mainly coming from online communities.Method: Our study has retrospectively studied (from 01/01/2015 to 03/11/2021)—using open access data—the association strength (using normalized mutual information) and the linear correlation (using Pearson’s correlation) between Twitter activity and cryptocurrency economical attributes. In addition, we have computed different models (ADF, ARIMA, and Interpretable MultiVvariable Long Short-Term Memory recurrent neural network) that forecast past price values and assessed their precision.Findings and conclusions: While the average Dogecoin transaction value is impacted by tweets, tweets are impacted by Litecoin transactions number and average Litecoin transaction value. Tweet number is impacted by Dogecoin whale behavior, but no significant relationship was found between Litecoin whales and tweets. The forecasting error resulting from our ARIMA (0,0,0) models was 0.08% (with Litecoin) and 0.22% (with Dogecoin). Therefore, those are just the beginning of scientific findings that may lead to building a trading robot based on these results. However, in itself, this study is only for academic discussion, and conclusions need to be drawn by further research. The authors cannot be liable if any financial investment is made based on its conclusions.

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The Anatomy of a Cryptocurrency Pump-and-Dump Scheme

Cited by 3 publications

References 16 publications

Identifying and Analyzing Cryptocurrency Manipulations in Social Media

Identifying and Analyzing Cryptocurrency Manipulations in Social Media

Vintage CryptoKitties and the Quest for Authenticity

Community Impact on a Cryptocurrency: Twitter Comparison Example Between Dogecoin and Litecoin

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