Position: AI/ML Influencers Have a Place in the Academic Process

TL;DR

This study demonstrates that social media influencers significantly boost citation counts for AI/ML research papers, highlighting their role in increasing research visibility and diversity in the academic community.

Contribution

It provides the first comprehensive causal analysis of social media influencers' impact on research citations and diversity in AI/ML publications.

Findings

Influencers increase median citations 2-3 times.

Significant diversity in highlighted authors.

Positive causal effect on paper visibility.

Abstract

As the number of accepted papers at AI and ML conferences reaches into the thousands, it has become unclear how researchers access and read research publications. In this paper, we investigate the role of social media influencers in enhancing the visibility of machine learning research, particularly the citation counts of papers they share. We have compiled a comprehensive dataset of over 8,000 papers, spanning tweets from December 2018 to October 2023, alongside controls precisely matched by 9 key covariates. Our statistical and causal inference analysis reveals a significant increase in citations for papers endorsed by these influencers, with median citation counts 2-3 times higher than those of the control group. Additionally, the study delves into the geographic, gender, and institutional diversity of highlighted authors. Given these findings, we advocate for a responsible approach to curation, encouraging influencers to uphold the journalistic standard that includes showcasing diverse research topics, authors, and institutions.