When Attention Becomes Exposure in Generative Search

TL;DR

This paper investigates how generative search engines tend to favor already prominent voices, especially in Web3 creator ecosystems, potentially reinforcing existing power structures and reducing diversity of viewpoints.

Contribution

It provides an empirical analysis of exposure bias in generative search citations, highlighting the influence of popularity and community concentration on visibility.

Findings

Popular voices receive more citation exposure.

Larger follower bases correlate with higher exposure.

Exposure bias may entrench incumbents and reduce diversity.

Abstract

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.