Relationship between Short-term Altmetric Changes and Long-term Citation: Multivariate Regression Analysis (Preprint)

BACKGROUND The methods for assessing the impact of academic papers are diversifying beyond traditional citation counts, with the rise of social media and online dissemination channels introducing alternative metrics (Altmetrics). These metrics capture influences not covered by traditional citations, reflecting a paper's dissemination on social media and online discussions. OBJECTIVE This study aims to explore the relationship between short-term changes in altmetrics indicators and long-term citation counts. METHODS We selected papers published in six high-impact journals (Cell, Nature, Science, JAMA, NEJM, and The Lancet) during 2019-2020. Data on altmetric mentions within 15 days after publication and citations were collected and transformed. The papers were grouped into high and low Altmetric Attention Score (AAS) categories, and multiple linear regression was used to analyze the relationship between early altmetric changes and later citation counts. RESULTS The analysis revealed a significant positive correlation between early AAS and later citation counts. Specific altmetric indicators, such as mentions on F1000, Facebook, news stories, patents, policy documents, and tweets, showed a strong positive correlation with citation frequency, while mentions on blogs and Reddit had a negative correlation. CONCLUSIONS Altmetrics provide immediate feedback on the impact and visibility of academic papers and can serve as early predictors of long-term citation trends. The study highlights the importance of various social media and online platforms in enhancing research visibility and underscores the potential of altmetrics as a valuable tool for comprehensive academic assessment. CLINICALTRIAL