Sentiment analysis is a growing research area in quantitative finance, especially with the advancement of Large Language Models (LLMs) and Natural Language Processing (NLP). Sentiment-based trading plays an important role in traditional finance; however, it is even more relevant in DeFi and crypto markets, which are known for their volatility and are significantly influenced by investor sentiment.
Reference [1] utilizes NLP to analyze sentiment in the crypto market and its impact on cryptocurrencies. Specifically, it investigates the relationship between sentiment in financial news articles and cryptocurrency price movements using natural language processing and statistical correlation analysis. The study consists of three phases: sentiment extraction, sentiment clustering, and correlation analysis.
The authors pointed out,
The study finds that Ethereum (ETH) has the strongest correlation between sentiment and price trends, with the hybrid sentiment correlation increasing from 0.3819 to 0.3900 over 24 hours…One possible explanation is Ethereum’s deep integration with DeFi applications and smart contracts, where sentiment-driven narratives (such as network upgrades, ecosystem developments, and new partnerships) significantly impact investor decisions.
Bitcoin exhibits a moderate sentiment correlation (0.2899 hybrid), which slightly increases after 12-24 hours. This suggests that while Bitcoin is affected by sentiment, other macroeconomic factors, institutional trading behaviors, and regulatory developments have a greater influence on its price.
Unlike Ethereum, Bitcoin has established itself as “digital gold” and a macroeconomic hedge, attracting a higher proportion of institutional investors, hedge funds, and long-term holders who base their decisions on fundamental and technical factors rather than short-term sentiment shifts. This makes BTC’s price less reactive to immediate sentiment fluctuations compared to ETH.
XRP demonstrates the weakest correlation with sentiment (0.1005 hybrid, increasing slightly to 0.1205 after 24 hours), suggesting that its price movements are largely disconnected from sentiment-based trading. A major reason for this weak correlation is XRP’s centralized development structure and reliance on partnerships with financial institutions.
In short, the article concluded that ETH shows the strongest sentiment-price correlation, BTC is moderately influenced, and XRP is the least impacted. Traders react to sentiment with a 12–24 hour lag, creating opportunities for predictive trading strategies.
Let us know what you think in the comments below or in the discussion forum.
References
[1] Franco Farrugia, Cedric Deguara, Sentiment Analysis and Cryptocurrency Price Correlation: A Data-Driven Study, MCAST Journal of Applied Research & Practice 2025; 9 (2) : 166-184
Post Source Here: Analyzing Crypto Market Sentiment with Natural Language Processing
source https://harbourfronts.com/analyzing-crypto-market-sentiment-natural-language-processing/
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