Generative search engines are reshaping information access by replacing traditional ranked lists with synthesized answers and references. In parallel, with the growth of Web3 platforms, incentive-driven creator ecosystems have become an essential part of how enterprises build visibility and community by rewarding creators for contributing to shared narratives. However, the extent to which exposure in generative search engine citations is shaped by external attention markets remains uncertain. In this study, we audit the exposure for 44 Web3 enterprises. First, we show that the creator community around each enterprise is persistent over time. Second, enterprise-specific queries reveal that more popular voices systematically receive greater citation exposure than others. Third, we find that larger follower bases and enterprises with more concentrated creator cores are associated with higher-ranked exposure. Together, these results show that generative search engine citations exhibit exposure bias toward already prominent voices, which risks entrenching incumbents and narrowing viewpoint diversity.
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.
This study provides a pioneering analysis of the features and topics of news websites in the Web 3.0 era through a comparison with non-news sites. We first classify over 4,600 Web3 sites into news and non-news types to investigate the feature characteristics of decentralized websites as well as semantic and subject categories. The most novel finding is that Web3 news sites have more features than non-news sites in terms of design systems and functions, interactivity, information quality, and hyperlinks. Furthermore, news web3 domains have more terms in semantic networks associated with information provision (e.g., “source”), whereas non-news domains have more terms associated with finance (e.g., “token”). The integration of the Decentralized Autonomous Organization, a fundamental component of the Web3 ecosystem, began in the news industry and is at an early stage in terms of functionality and structure. The study’s results are discussed in the context of future Web3 domain development.
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