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

Iain Weissburg, Mehir Arora, Xinyi Wang, Liangming Pan, William Yang Wang
Proceedings of the 41st International Conference on Machine Learning, PMLR 235:52680-52694, 2024.

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.

Cite this Paper

BibTeX
@InProceedings{pmlr-v235-weissburg24a, title = {Position: {AI}/{ML} Influencers Have a Place in the Academic Process}, author = {Weissburg, Iain and Arora, Mehir and Wang, Xinyi and Pan, Liangming and Wang, William Yang}, booktitle = {Proceedings of the 41st International Conference on Machine Learning}, pages = {52680--52694}, year = {2024}, editor = {Salakhutdinov, Ruslan and Kolter, Zico and Heller, Katherine and Weller, Adrian and Oliver, Nuria and Scarlett, Jonathan and Berkenkamp, Felix}, volume = {235}, series = {Proceedings of Machine Learning Research}, month = {21--27 Jul}, publisher = {PMLR}, pdf = {https://raw.githubusercontent.com/mlresearch/v235/main/assets/weissburg24a/weissburg24a.pdf}, url = {https://proceedings.mlr.press/v235/weissburg24a.html}, 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.} }
Endnote
%0 Conference Paper %T Position: AI/ML Influencers Have a Place in the Academic Process %A Iain Weissburg %A Mehir Arora %A Xinyi Wang %A Liangming Pan %A William Yang Wang %B Proceedings of the 41st International Conference on Machine Learning %C Proceedings of Machine Learning Research %D 2024 %E Ruslan Salakhutdinov %E Zico Kolter %E Katherine Heller %E Adrian Weller %E Nuria Oliver %E Jonathan Scarlett %E Felix Berkenkamp %F pmlr-v235-weissburg24a %I PMLR %P 52680--52694 %U https://proceedings.mlr.press/v235/weissburg24a.html %V 235 %X 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.
APA
Weissburg, I., Arora, M., Wang, X., Pan, L. & Wang, W.Y.. (2024). Position: AI/ML Influencers Have a Place in the Academic Process. Proceedings of the 41st International Conference on Machine Learning, in Proceedings of Machine Learning Research 235:52680-52694 Available from https://proceedings.mlr.press/v235/weissburg24a.html.

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