Popular orthodontic research on Twitter/X: are scholars and the public in sync?

Objectives This study aimed at mapping bibliometric networks and analysing citation impact of the most popular orthodontic articles on Twitter/X. Methods The top 100 original research articles and systematic reviews/meta-analyses with the most tweets published in the orthodontic journals included in Journal Citation Reports 2023 were retrieved from Altmetric Explorer. Associations were investigated using a random forest algorithm (Boruta) between publication details, Altmetric Attention Score (AAS) and X posts or Web of Science (WoS) citations while co-authorship and keyword networks were visualized using VOSviewer software. Results The sample of most-tweeted articles were assigned a median AAS of 7 [interquartile range (IQR); 5, 14], 8 (IQR; 6, 11) X posts and 21 (IQR; 8, 44) WoS citations. Most of the articles referred to human research, originated from European affiliations, authored by more than four scholars, and were published within 10 years prior to search date. AAS and time since publication were confirmed as important article attributes in predicting the number of X posts. Article type, subject, and time since publication were important factors in predicting WoS citation counts received. Conclusions Top 100 orthodontic articles on X involved clinical studies and broad author collaborations. Citation count prediction could not be indicated by the popularity of articles on the platform. X engagement and research priorities of scholars need to be re-evaluated to increase the public relevance of orthodontic research.