Social Media Mentions are a Stronger Predictor of Citations than 5-Year Impact Factor in Neurosurgical Research.

Background And Objectives: X (formerly known as Twitter) is a social media platform gaining popularity in neurosurgery. Other disciplines have demonstrated a positive correlation between Twitter activity and traditional citation metrics. This study aims to determine if X activity is a greater predictor of citation rates than a journal's 5-year impact factor (IF) among major neurosurgical journals.

Methods: Using a mixed linear model, we compared the predictive value between alternative metrics (such as mentions on X and Altmetric attention score, a weighted aggregate of the attention an article receives on various platforms) and traditional citation metrics (5-year journal IF) on the number of citations an article received by analyzing 7592 articles published from January 2022 to December 2023 in 18 neurosurgical journals. It was necessary to also account for the confounding variable time since publication in the model to determine the true effect of altmetrics. The relative importance (RI) of each predictor variable was determined through permutation testing.

Results: X mentions, time since publication, 5-year journal IF, and Altmetric attention score all significantly predict citation rates (P < .001). RI of X mentions on citation rates indicate that X (RI = 0.13) is approximately 8.7x times greater of a predictor of citations than 5-year IF (RI = 0.015) and 5.4x times greater of a predictor than the Altmetric attention score (RI = 0.024). Time of publication remains the strongest predictor (RI = 0.83).

Conclusion: Our study shows that in neurosurgical research, while social media mentions (X mentions) are significant, they are weaker predictors of citation rates than time since publication. Traditional journal IF and Altmetric attention scores have weaker predictive value. These findings indicate that altmetrics, especially X mentions, can complement traditional citation metrics.