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 1:1 matched controls based on publication year, venue, and abstract topics. Our 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. These findings highlight the expanding influence of social media in scholarly communication and underscore the importance of an evolving ecosystem in today's digital academic landscape.

翻译：随着人工智能和机器学习会议接收论文数量达到数千篇，研究人员获取和阅读研究出版物的情况已变得不再明朗。本文探讨了社交媒体影响者在提升机器学习研究可见度方面的作用，特别是其分享论文的引用次数。我们编制了一个包含8000多篇论文的综合数据集，涵盖2018年12月至2023年10月的推文，并根据出版年份、会议及摘要主题按1:1匹配了对照组。分析显示，受这些影响者推荐的论文引用次数显著增加，其中位数引用次数是对照组的2-3倍。此外，研究还深入分析了被突出作者的地理、性别和机构多样性。这些发现凸显了社交媒体在学术交流中日益增长的影响力，并强调了当今数字学术格局中不断演进的生态系统的重要性。