Abstract:

This study delves into the dynamic landscape of public sentiment surrounding cryptocurrency through a comprehensive social media discourse analysis. Employing the Python Selenium library, data from 1000 public profiles across major platforms—X, Facebook, Instagram, and LinkedIn—were systematically collected. Using advanced text-mining techniques in R Studio, sentiment analysis was conducted with the ‘Syuzhet’ package and word frequency analysis via the ‘tm’ package. The results unveiled a nuanced emotional landscape characterized by dominant sentiments of anticipation and positivity, interwoven with expressions of negativity, notably anger, and loss. Word frequency analysis highlighted vital themes such as established cryptocurrencies (e.g., Bitcoin, Ethereum), blockchain technology, and practical and financial aspects of cryptocurrency usage. The study illuminated technical interest, financial speculation, and reactions to regulatory and economic developments. Offering insights crucial for stakeholders, including investors and policymakers, this research contributes to the academic understanding of public sentiment, emphasizing the volatile nature of crypto-currency markets and the transformative potential of blockchain technology and calls for ongoing monitoring of public sentiment to inform policy, investment, and technological innovation in the ever-evolving cryptocurrency ecosystem.

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