Tweets to Citations: Unveiling the Impact of Social Media Influencers on AI Research Visibility
CoRR(2024)
摘要
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.
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