Vineeth Kumar Reddy Anumula and Niskhep A Kulli, Sacred Heart University, USA

In the light of heightened geopolitical and economic volatility, conversation around de-dollarization and the rise of alternative currencies has intensified, sparking widespread pub- lic debate. This article builds on analyzing 6000 tweets retrieved from platform X, utilizing ad- vanced natural language processing (NLP) techniques—sentiment analysis, tweet classification us- ing BERT (Bidirectional Encoder Representations from Transformers), named entity recognition (NER), and Latent Dirichlet Allocation (LDA) modeling—to delve into these critical discussions. This study uncovers key entities and other emerging financial technologies, revealing a complex and evolving narrative. The findings underscore the critical role of social media as a barometer for global economic trends, particularly in light of ongoing debates surrounding currency alternatives. With geopolitical tensions mounting, the discourse on financial sovereignty, cryptocurrencies, and national economic strategies is becoming increasingly polarized. Sentiment analysis reveals stark contrasts in public opinion, while LDA modeling uncovers dominant themes driving the conversa- tion. This research is especially timely, as the growing intensity of discussions on currency dominance and financial security demands a more nuanced understanding. By offering a real-time analysis of these debates, this paper provides essential insights for policymakers, economists, and academics. As the global financial landscape shifts, our findings serve as a crucial layer in the academic dis- course, revealing how technology, public opinion, and geopolitics intertwine to shape the future of global economies.

Natural language processing, NLP, Currency, Sentiment analysis, Entity recognition, Latent Dirichlet Allocation(LDA), De-Dollarization.