Direct and Indirect Influence of Altmetrics on Citation in Social Systems: Assessing a New Conceptual Model

This study aimed to assess the paths through which save metrics (on CiteULike, Mendeley, and Figshare) and discussion metrics (on Twitter, Facebook, and Wikipedia) influence citation. This descriptive-correlation study investigates the relationships between different variables based on its proposed conceptual model. Systematic and stratified sampling was employed and, using the Cochrane formula, the sample size was determined to be 1892 articles. Data were collected using the PLOS altmetrics, and path analysis was administered to test the conceptual model by using AMOS software. The results convey that Mendeley was the most effective path resulting to citation. Mendeley has a positive and significant relationship with citation via save as an intermediator. Twitter also had a negative and significant relationship with citation via discussion as an intermediating factor. Yet, neither save metrics on CiteULike and Figshare nor discussion on Facebook and Wikipedia does create a path of influence on citation. Identifying the effective paths through which social networks affect citation via altmetrics and presenting a final model of those paths could enrich and expand the theoretical foundations in the field of altmetrics. Besides identifying the most effective social networks and paths for online scientific interactions that lead to citation, the implications of this research can provide deeper insights for policy makers, editors and scholars.