From HODL to MOON: Understanding Community Evolution, Emotional Dynamics, and Price Interplay in the Cryptocurrency Ecosystem

• URL: http://arxiv.org/abs/2312.08394v1
• Date: Tue, 12 Dec 2023 19:56:36 GMT
• Title: From HODL to MOON: Understanding Community Evolution, Emotional Dynamics, and Price Interplay in the Cryptocurrency Ecosystem
• Authors: Kostantinos Papadamou, Jay Patel, Jeremy Blackburn, Philipp Jovanovic, Emiliano De Cristofaro
• Abstract summary: 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.
• Score: 13.409057009695513
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: This paper presents a large-scale analysis of the cryptocurrency community on Reddit, shedding light on the intricate relationship between the evolution of their activity, emotional dynamics, and price movements. We analyze over 130M posts on 122 cryptocurrency-related subreddits using temporal analysis, statistical modeling, and emotion detection. While /r/CryptoCurrency and /r/dogecoin are the most active subreddits, we find an overall surge in cryptocurrency-related activity in 2021, followed by a sharp decline. We also uncover a strong relationship in terms of cross-correlation between online activity and the price of various coins, with the changes in the number of posts mostly leading the price changes. Backtesting analysis shows that a straightforward strategy based on the cross-correlation where one buys/sells a coin if the daily number of posts about it is greater/less than the previous would have led to a 3x return on investment. Finally, we shed light on the emotional dynamics of the cryptocurrency communities, finding that joy becomes a prominent indicator during upward market performance, while a decline in the market manifests an increase in anger.

Related papers

• Interplay between Cryptocurrency Transactions and Online Financial Forums [41.94295877935867]
  This study focuses on the study of the interplay between these cryptocurrency forums and fluctuations in cryptocurrency values. It shows that the activity of Bitcointalk forum keeps a direct relationship with the trend in the values of BTC. The experiment highlights that forum data can explain specific events in the financial field.
  arXiv  Detail & Related papers  (2023-11-27T16:25:28Z)
• AI-Assisted Investigation of On-Chain Parameters: Risky Cryptocurrencies and Price Factors [0.9831489366502302]
  This paper focuses on analyzing historical data and using artificial intelligence algorithms on on-chain parameters. We conducted an analysis of historical cryptocurrencies' on-chain data and measured the correlation between the price and other parameters. Our analysis revealed a significant negative correlation between cryptocurrency price and maximum and total supply, as well as a weak positive correlation between price and 24-hour trading volume.
  arXiv  Detail & Related papers  (2023-08-11T09:20:28Z)
• Identifying key players in dark web marketplaces [58.720142291102135]
  This paper aims to identify the key players in Bitcoin transaction networks linked to dark markets. We show that a large fraction of the traded volume is concentrated in a small group of elite market participants. Our findings suggest that understanding the behavior of key players in dark web marketplaces is critical to effectively disrupting illegal activities.
  arXiv  Detail & Related papers  (2023-06-15T20:30:43Z)
• Understanding Cryptocoins Trends Correlations [0.76146285961466]
  We shed light on the trend correlations across a large variety of cryptocoins, by investigating their coin-price correlation trends over a period of two years. Our results suggest strong correlation patterns between main coins (Ethereum, Bitcoin) and alt-coins. We believe our study can support forecasting techniques for time-series modeling in the context of crypto-coins.
  arXiv  Detail & Related papers  (2022-11-30T15:50:36Z)
• Token Spammers, Rug Pulls, and SniperBots: An Analysis of the Ecosystem of Tokens in Ethereum and the Binance Smart Chain (BNB) [50.888293380932616]
  We study the ecosystem of the tokens and liquidity pools, highlighting analogies and differences between the two blockchains. We estimate the lifetime of the tokens, discovering that about 60% of them are active for less than one day. We present an exit scam fraud and quantify its prevalence on both blockchains.
  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 [63.732639864601914]
  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 of pump and dump. Then, we leverage our unique dataset of the verified pump and dumps to build a machine learning model able to detect a pump and dump in 25 seconds from the moment it starts.
  arXiv  Detail & Related papers  (2021-05-03T10:20:47Z)
• A Sentiment Analysis Approach to the Prediction of Market Volatility [62.997667081978825]
  We have explored the relationship between sentiment extracted from financial news and tweets and FTSE100 movements. The sentiment captured from news headlines could be used as a signal to predict market returns; the same does not apply for volatility. We developed an accurate classifier for the prediction of market volatility in response to the arrival of new information.
  arXiv  Detail & Related papers  (2020-12-10T01:15:48Z)
• Pump and Dumps in the Bitcoin Era: Real Time Detection of Cryptocurrency Market Manipulations [63.732639864601914]
  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.