Dogecoin's market cap grew six-fold in January 2021 after tweets from Tesla CEO Elon Musk, and has kept on growing since. By February 2021, the market cap of the cryptocurrency based on the famous internet meme had already doubled again. Compared to both the Bitcoin market capitalization as well as the Ethereum market cap, Dogecoin was not as popular.

The price of the cryptocurrency based on the famous internet meme broke its price decline in early November 2022 - as people started buying the coin after FTX's collapse. This rally only lasted for a few days, however, as a Dogecoin was worth roughly 0.17 U.S. dollars on May 4, 2025. This is a different development than in 2021 - when the crypto became very popular in a short amount of time. Between January 28 and January 29, 2021, Dogecoin's value grew by around 216 percent to 0.023535 U.S. dollars after comments from Tesla CEO Elon Musk. The digital coin quickly grew to become the most talked-about cryptocurrency available: not necessarily for its price - the prices of Bitcoin (BTC), Ethereum (ETH), Ripple (XRP) and several other virtual currencies were much higher than that of DOGE - but for its growth.

The market cap of the top 10 stablecoin initially multiplied over time, reaching a combined value of over 221 billion USD in May 2025. Note this value does not include TerraUSD (UST), the algorithmic stablecoin tied to the LUNA crypto which declined severely in May 2022. Up to then, estimates reveal that the market cap had more than tripled within five months - likely following growing interest worldwide in cryptocurrencies, after sudden price spikes in a coin like Dogecoin (DOGE). Stability above all, or what does a stablecoin do? Stablecoins are cryptocurrencies - like the commonly known Bitcoin (BTC) and Ethereum (ETH) - but their value is determined differently. Whilst the price of Bitcoin mainly follows supply - how many coins are being mined or are available to purchase - and demand - how many investors want to buy the coin - stablecoins are synthetically connected to the price of an altogether different asset. Tether's USDT, for instance, is connected to the price development of the U.S. dollar (USD): if the U.S. dollar falls in the FX market, so does the USDT. Compare this to the "regular" price history of a cryptocurrency like Ripple (XRP) and stablecoins reveal themselves to be a relatively less volatile digital currency to either use or invest in than their counterparts in the free market. A test ground for digital payments This stability of these particular cryptocurrencies is important for two areas in digital payments that do not prefer volatility. For instance, these coins are a popular choice within the world of Decentralized Finance or DeFi - an online financial market without the supervision of central bank that relies on cryptocurrencies for payments and loans. Because of that reliance, it is a market that can rapidly change in size due to price fluctuations or changing transaction fees of certain cryptocurrencies - something that is less likely to occur when using stablecoins. Additionally, stablecoins are considered the inspiration for so-called CBDC or Central Bank Digital Currencies - such as China's e-CNY currency or the "digital euro" that is being researched in the EU-27. In terms of how advanced countries worldwide are into researching their own cryptocurrency, China ranked third in 2020, behind Cambodia, and The Bahamas.

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.

Cryptocurrency historical datasets from January 2012 (if available) to October 2021 were obtained and integrated from various sources and Application Programming Interfaces (APIs) including Yahoo Finance, Cryptodownload, CoinMarketCap, various Kaggle datasets, and multiple APIs. While these datasets used various formats of time (e.g., minutes, hours, days), in order to integrate the datasets days format was used for in this research study. The integrated cryptocurrency historical datasets for 80 cryptocurrencies including but not limited to Bitcoin (BTC), Ethereum (ETH), Binance Coin (BNB), Cardano (ADA), Tether (USDT), Ripple (XRP), Solana (SOL), Polkadot (DOT), USD Coin (USDC), Dogecoin (DOGE), Tron (TRX), Bitcoin Cash (BCH), Litecoin (LTC), EOS (EOS), Cosmos (ATOM), Stellar (XLM), Wrapped Bitcoin (WBTC), Uniswap (UNI), Terra (LUNA), SHIBA INU (SHIB), and 60 more cryptocurrencies were uploaded in this online Mendeley data repository. Although the primary attribute of including the mentioned cryptocurrencies was the Market Capitalization, a subject matter expert i.e., a professional trader has also guided the initial selection of the cryptocurrencies by analyzing various indicators such as Relative Strength Index (RSI), Moving Average Convergence/Divergence (MACD), MYC Signals, Bollinger Bands, Fibonacci Retracement, Stochastic Oscillator and Ichimoku Cloud. The primary features of this dataset that were used as the decision-making criteria of the CLUS-MCDA II approach are Timestamps, Open, High, Low, Closed, Volume (Currency), % Change (7 days and 24 hours), Market Cap and Weighted Price values. The available excel and CSV files in this data set are just part of the integrated data and other databases, datasets and API References that was used in this study are as follows: [1] https://finance.yahoo.com/ [2] https://coinmarketcap.com/historical/ [3] https://cryptodatadownload.com/ [4] https://kaggle.com/philmohun/cryptocurrency-financial-data [5] https://kaggle.com/deepshah16/meme-cryptocurrency-historical-data [6] https://kaggle.com/sudalairajkumar/cryptocurrencypricehistory [7] https://min-api.cryptocompare.com/data/price?fsym=BTC&tsyms=USD [8] https://min-api.cryptocompare.com/ [9] https://p.nomics.com/cryptocurrency-bitcoin-api [10] https://www.coinapi.io/ [11] https://www.coingecko.com/en/api [12] https://cryptowat.ch/ [13] https://www.alphavantage.co/ This dataset is part of the CLUS-MCDA (Cluster analysis for improving Multiple Criteria Decision Analysis) and CLUS-MCDAII Project: https://aimaghsoodi.github.io/CLUSMCDA-R-Package/ https://github.com/Aimaghsoodi/CLUS-MCDA-II https://github.com/azadkavian/CLUS-MCDA

Somewhat resembling developments of Dogecoin in early 2021, the market cap of Shiba Inu (SHIB) more than tripled in only a few weeks. This rapid growth especially occurred since September 2021, with the cryptocurrency breaking the 10 billion U.S. dollar barrier multiple in the following month. Whilst no exact reason was given why the memecoin grew so fast during this time, the digital currency did become available on Coinbase, one of the world's most well-known crypto exchanges, on September 17. This move, and the fact that consumers in the U.S. and the UK overall tend to invest in crypto for fun or as a potential growth investment, might explain the popularity of the dog-themed coin. Indeed, Shiba Inu ranked as the number 13 cryptocurrency in the world based on market cap in late October 2021 - closely behind DeFi-affilated like Uniswap (UNI) and Terra (LUNA).

Memecoin Shiba Inu saw its price grow by more than 300 percent within one and the same month, marking a trading fury reminiscent of Dogecoin in early 2021. Indeed, the SHIB coin ranked as one of the biggest crypto in the world based on 24h trading volume in October 2021 - with trading activity being almost as high as that of Ethereum. Originally starting out as a fun token based on the famous Japanese dog breed, the digital currency grabbed mainstream attention in 2021 probably due to its low barrier of entry: Even after its price spikes, Shiba Inu was one of the cheapest coins available, especially when compared to the price of 99 other cryptocurrencies. Combine this with survey information that most consumers in the U.S. and the UK invest in crypto either for growth or fun, and Shiba Inu is probably seen by many as a relatively simple, "quick win" investment. As of May 19, 2025, the price of one million Shiba Inu is 14.08.

Based on Google searches, consumers from Africa and Latin America made up eight of the top 10 countries with the most interest in Bitcoin in 2020. This according to information that was compiled from Google Trends, which compared searches with the keyword "Bitcoin" against searches for nine other cryptocurrencies - Bitcoin Cash, Cardano, Dogecoin, Ethereum, IOTA, Litecoin, Monero, XRP, and Tron. Bitcoin search interest was especially high in Kenya, whilst Nigeria and South Africa were fifth and sixth in a ranking that compares the 55 different countries against each other. Note that the figures provided here were from before the surge in both the price of Bitcoin as well as the Bitcoin market cap observed at the end of 2020 and early 2021.