Exploring the Social Media Wave of Halal Cryptocurrency Sentiment: A Natural Language Processing Approach

Abstract

Cryptocurrency's popularity is primarily driven by user trends and Central Bank Digital Currency initiatives. However, specific Islamic communities identified vary in comprehension of halal and haram due to level and Shariah compliance discrepancies. This study seeks to understand the Muslim community’s perspective on halal cryptocurrency on X, Instagram, Facebook, TikTok, and YouTube. This study has gathered and studied 11,059 comments based on a Natural Language Processing (NLP) approach. This study also uses data triangulation, achieved by intercoder agreement and with a series of complementary studies: word clouds, tree maps, Sankey diagrams, and sentiment layers using the ATLAS software. The results demonstrated that, on social media, issues and terms related to crypto have a high frequency of pronunciation and interpretation. Based on sentiment analysis, 76.92% of comments expressed a negative sentiment, and 23.08% of comments expressed a positive sentiment toward halal cryptocurrency. The research also focuses on the intersection of sentiment analysis and other models and theories of new technology acceptance. This research has its constraints with regard to social media.