Mapping Spreader Roles in Web3 Discourse: Network Analysis and Topic Modeling of NFT and DeFi Communities

Abstract

Web3 technologies, notably Non-Fungible Tokens (NFTs) and Decentralized Finance (DeFi), have generated extensive social media discourse. This study integrates Social Network Analysis (SNA) and BERTopic to examine spreader roles in shaping Web3 conversations on platform X. We collected 12,925 NFT and 7,087 DeFi posts from August 23 to September 23, 2025, using domain-specific keywords. Data preprocessing removed duplicates, spam, and irrelevant content through URL stripping, hashtag filtering, and manual verification of top spreaders to exclude automated accounts. All collection adhered to X's Terms of Service using publicly available English-language posts without personal identifying information. In-degree centrality analysis identified top spreaders. @GiveRep in NFT achieved a time reached of 288 hours with an average propagation speed of two hours, while @BioProtocol in DeFi demonstrated a uniform persistence of 192 hours uniform persistence across top actors. BERTopic analysis revealed thematic differences. NFT discussions centered on community engagement and speculation, whereas DeFi discourse concentrated on protocol infrastructure and yield mechanisms. NFT spreaders exhibited varied influence duration aligned with thematic diversity, while DeFi spreaders showed uniform persistence constrained by content overlap. This integrated framework advances computational social research methodologies and offers practical insights for Web3 stakeholders to identify key influencers and optimize community engagement strategies. Limitations include single-platform focus and one-month observation period.