A Few Social Media Influencers Are Shaping AI

The term “social media influencer” may call to mind Instagram accounts shilling hair growth gummies and cute outfits—but in reality, influencers influence all types of things. Including artificial intelligence research trends.

Mainstream interest in AI and machine learning is at an all-time high, and the industry is responding—churning out thousands of AI and ML works for conferences and journals. The AI/ML community is also particularly active in posting non-peer-reviewed preprints via online platforms like ArXiv. Given this glut of work, what rises to the top and receives attention?

The answer, at least in part, is: the research that a pair of highly influential users of X (formerly Twitter) choose to highlight, according to a new preprint from researchers at University of California at Santa Barbara.

The UCSB paper analyzed more than 8,000 AI and ML papers, considering both social media mentions and the number of citations. Reviewing tweets from December 2018 to October 2023, the researchers concluded AI/ML papers shared by two specific influencers had median citation counts two to three times higher than those of the control group.

This is crucial because academic citations aren’t just about recognition in one’s field; they also affect decisions like research funding and tenure at academic institutions. And it’s a change from the status quo. As recently as 2018, a study of conference papers showed that a paper’s review score—meaning acceptance to top conferences—was a primary indicator of future citation count.

Now, “the correlation between influencer tweets and citation count—and not review scores—points to a shift in how the community finds and reads papers,” this new work concludes.

Two influencers with an outsized effect on AI

The researchers selected two influencers as case studies. Both share AI/ML papers consistently and have a significant following on X (formerly Twitter): @_akhaliq and @arankomatsuzaki. “These influencers have emerged as pivotal figures in navigating the flood of information, akin to journalists in civic society, highlighting and contextualizing significant works for the community,” the authors write.

That curation is a helpful—and, of course, unpaid—service from these influencers given the deluge of research. But “an over-reliance on a select group of curators may inadvertently skew the research landscape, emphasizing certain topics or perspectives over others,” the researchers write. Inadvertent bias in sharing certain labs’ or researchers’ work may entrench a lack of geographic, gender, and/or institutional diversity, the paper adds.

Awareness is the first step to busting this social media echo chamber, says lead author Iain Xie Weissburg, a first-year master’s student in UCSB’s Electrical and Computer Engineering program.

“We wanted to help the community recognize this and be vigilant in ensuring that research remains an evenly leveled domain,” he tells Spectrum. “As…