Web3 technologies—comprising decentralized finance (DeFi), non-fungible tokens (NFTs), and decentralized autonomous organizations (DAOs)—spark significant public discourse, balancing enthusiasm for innovation with skepticism about associated challenges. While previous studies focus on specific Web3 domains, they often overlook the interplay between thematic discussions and emotional traits, limiting insights into adoption dynamics. This study bridges that gap using a two-stage methodology: Stage 1 categorizes Web3 discussions into industries (e.g., Core Infrastructure, DeFi, NFTs, DAOs), and Stage 2 analyzes emotional traits namely optimism, skepticism, frustration, curiosity, and concern. Annotated data from X (formerly Twitter), YouTube, and Reddit are classified using fine-tuned Bidirectional Encoder Representations from Transformers (BERT) models, achieving macro F1-scores of 0.82 for thematic and 0.84 for emotional classification. Findings reveal that curiosity and optimism dominate Core Infrastructure and Decentralized applications (DApps) discussions, while frustration is more prevalent in NFTs and DAOs. These insights provide actionable strategies for addressing barriers and amplifying drivers of Web3 adoption. Future research should explore broader demographic and temporal trends or employ advanced transformer models like the Robustly Optimized BERT Pretraining Approach (RoBERTa) and XLNet to enhance accuracy and depth.