Determine how researchers access and read AI/ML research publications in the online era

Determine the modalities and patterns by which researchers in artificial intelligence and machine learning access and read research publications in the contemporary environment characterized by widespread online preprint sharing (e.g., arXiv) and social media dissemination, in order to understand the evolving relevance and reception of papers outside traditional academic forums.

Background

The paper motivates its paper by noting the rapid growth in AI/ML publications and the increasing use of online preprint platforms and social media, which may have altered how research is discovered and consumed. The authors focus on influencer-driven dissemination on social media as one mechanism shaping visibility and impact, but they highlight uncertainty around the broader processes by which researchers access and read publications in this new landscape.

This uncertainty serves as a foundational question that contextualizes their empirical analysis of influencer sharing and citations, suggesting a need for systematic understanding of reading and access behaviors in the AI/ML community amid changing dissemination channels.