Measuring Memecoin Fragility

• URL: http://arxiv.org/abs/2512.00377v1
• Date: Sat, 29 Nov 2025 08:11:51 GMT
• Title: Measuring Memecoin Fragility
• Authors: Yuexin Xiang, SM Mahir Shazeed Rish, Qishuang Fu, Yuquan Li, Qin Wang, Tsz Hon Yuen, Jiangshan Yu,
• Abstract summary: We present the first Memecoin Ecosystem Fragility Framework (ME2F)<n>ME2F formalizes memecoin risks in three dimensions.<n>We show that fragility is not evenly distributed across the ecosystem.
• Score: 6.920310979114652
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: Memecoins, emerging from internet culture and community-driven narratives, have rapidly evolved into a unique class of crypto assets. Unlike technology-driven cryptocurrencies, their market dynamics are primarily shaped by viral social media diffusion, celebrity influence, and speculative capital inflows. To capture the distinctive vulnerabilities of these ecosystems, we present the first Memecoin Ecosystem Fragility Framework (ME2F). ME2F formalizes memecoin risks in three dimensions: i) Volatility Dynamics Score capturing persistent and extreme price swings together with spillover from base chains; ii) Whale Dominance Score quantifying ownership concentration among top holders; and iii) Sentiment Amplification Score measuring the impact of attention-driven shocks on market stability. We apply ME2F to representative tokens (over 65\% market share) and show that fragility is not evenly distributed across the ecosystem. Politically themed tokens such as TRUMP, MELANIA, and LIBRA concentrate the highest risks, combining volatility, ownership concentration, and sensitivity to sentiment shocks. Established memecoins such as DOGE, SHIB, and PEPE fall into an intermediate range. Benchmark tokens ETH and SOL remain consistently resilient due to deeper liquidity and institutional participation. Our findings provide the first ecosystem-level evidence of memecoin fragility and highlight governance implications for enhancing market resilience in the Web3 era.

Related papers

• MemeChain: A Multimodal Cross-Chain Dataset for Meme Coin Forensics and Risk Analysis [52.468043639056596]
  The meme coin ecosystem has grown into one of the most active yet least observable segments of the cryptocurrency market.<n>MemeChain integrates on-chain data with off-chain artifacts, including website HTML source code, token logos, and linked social media accounts.<n>We quantify the ecosystem's extreme volatility, identifying 1,801 tokens (5.15%) that cease all trading activity within just 24 hours of launch.
  arXiv  Detail & Related papers  (2026-01-28T14:42:02Z)
• The Memecoin Phenomenon: An In-Depth Study of Solana's Blockchain Trends [0.0]
  Using on-chain data, it is explored how retail-focused token creation platforms are reshaping blockchain ecosystems.<n>Pump$.$fun accounted for up to 71.1% of all tokens minted on Solana and contributed 40-67.4% of total DEX transactions.<n>This paper highlights the need to critically assess the implications of retail-driven speculative trading and its potential to disrupt emerging blockchain economies.
  arXiv  Detail & Related papers  (2025-12-04T16:06:22Z)
• A Midsummer Meme's Dream: Investigating Market Manipulations in the Meme Coin Ecosystem [57.92093214580746]
  We characterize the tokenomics of meme coins and track their growth in a three-month longitudinal analysis.<n>We find evidence of extensive use of artificial growth strategies designed to create a misleading appearance of market interest.<n>Most of the tokens involved had previously experienced wash trading or LPI, indicating how initial manipulations often set the stage for later exploitation.
  arXiv  Detail & Related papers  (2025-04-16T13:54:42Z)
• A Sea of Coins: The Proliferation of Cryptocurrencies in UniswapV2 [0.8192907805418583]
  We analyze the financial impact of newly created tokens, assessing their market dynamics, profitability and liquidity manipulations.<n>Applying a simple buy-and-hold strategy, we are able to uncover some major risks associated with investing in newly created tokens.<n>Our study provides insights into the risks and financial dynamics of decentralized markets and their challenges for investors.
  arXiv  Detail & Related papers  (2025-02-14T19:18:39Z)
• Memes, Markets, and Machines: The Evolution of On Chain Autonomy through Hyperstition [0.0]
  Zerebro, an AI fine-tuned on schizophrenic responses, autonomously creates and spreads disruptive memes. Based on our research, Zerebro is the first cross-chain AI, seamlessly interacting with multiple blockchains. This study uncovers how hyperstition, fictions becoming reality through viral propagation, emerges in AI, driven meme culture and decentralized finance.
  arXiv  Detail & Related papers  (2024-10-31T10:26:49Z)
• IT Strategic alignment in the decentralized finance (DeFi): CBDC and digital currencies [49.1574468325115]
  Decentralized finance (DeFi) is a disruptive-based financial infrastructure. This paper seeks to answer two main questions 1) What are the common IT elements in the DeFi? And 2) How the elements to the IT strategic alignment in DeFi?
  arXiv  Detail & Related papers  (2024-05-17T10:19:20Z)
• From HODL to MOON: Understanding Community Evolution, Emotional Dynamics, and Price Interplay in the Cryptocurrency Ecosystem [13.409057009695513]
  We analyze over 130M posts on 122 cryptocurrency-related subreddits on Reddit. We find an overall surge in cryptocurrency-related activity in 2021, followed by a sharp decline. We find that joy becomes a prominent indicator during upward market performance, while a decline in the market manifests an increase in anger.
  arXiv  Detail & Related papers  (2023-12-12T19:56:36Z)
• Token Spammers, Rug Pulls, and SniperBots: An Analysis of the Ecosystem of Tokens in Ethereum and in the Binance Smart Chain (BNB) [50.888293380932616]
  We study the ecosystem of the tokens and liquidity pools. We find that about 60% of tokens are active for less than one day. We estimate that 1-day rug pulls generated $240 million in profits.
  arXiv  Detail & Related papers  (2022-06-16T14:20:19Z)
• Cryptocurrency Bubble Detection: A New Stock Market Dataset, Financial Task & Hyperbolic Models [31.690290125073197]
  We present and publicly release CryptoBubbles, a novel multi-span identification task for bubble detection. We develop a set of sequence-to-sequence hyperbolic models suited to this multi-span identification task. We show the practical applicability of CryptoBubbles and hyperbolic models on Reddit and Twitter.
  arXiv  Detail & Related papers  (2022-05-11T08:10:02Z)
• The Doge of Wall Street: Analysis and Detection of Pump and Dump Cryptocurrency Manipulations [50.521292491613224]
  This paper performs an in-depth analysis of two market manipulations organized by communities over the Internet: The pump and dump and the crowd pump. The pump and dump scheme is a fraud as old as the stock market. Now, it got new vitality in the loosely regulated market of cryptocurrencies. We report on three case studies related to pump and dump groups.
  arXiv  Detail & Related papers  (2021-05-03T10:20:47Z)
• Pump and Dumps in the Bitcoin Era: Real Time Detection of Cryptocurrency Market Manipulations [50.521292491613224]
  We perform an in-depth analysis of pump and dump schemes organized by communities over the Internet. We observe how these communities are organized and how they carry out the fraud. We introduce an approach to detect the fraud in real time that outperforms the current state of the art.
  arXiv  Detail & Related papers  (2020-05-04T21:36:18Z)

This list is automatically generated from the titles and abstracts of the papers in this site.

This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.