Measuring Social Media Performance Efficiency of High-Impact Library and Information Science Journals

A Data Envelopment Analysis Approach

Abstract

Background: The connection between social media and scholarly communication has become a vital instrument for expanding knowledge dissemination. However, the effectiveness of digital utilization by academic Library and Information Science (LIS) journals has not been maximally measured, leaving a gap in understanding how well these journals leverage social platforms to amplify their research impact.
Purpose: This study aims to evaluate the social media performance efficiency of reputable LIS journals (SJR > 1) by measuring how effectively academic inputs are converted into digital visibility outputs.
Methods: The study employs Data Envelopment Analysis (DEA) using the BCC-Output Oriented model. Ten selected LIS journals were analyzed as Decision Making Units (DMUs). Input variables included the Article Processing Charge (APC), H-Index, and number of citations, while output variables consisted of mentions on X (Twitter) and Facebook.
Findings: The results revealed a clear performance polarization: 50% of the journals (5 DMUs) achieved perfect efficiency (score 1.00), while the remaining 50% were inefficient in converting academic resources into digital visibility. Additionally, X (Twitter) emerged as the dominant dissemination platform compared to Facebook.
Originality/Value: This study offers a novel efficiency-based approach to assessing social media performance among high-impact LIS journals, an area previously unmeasured through quantitative benchmarking. It provides actionable recommendations for publishers, notably the appointment of dedicated social media editors, to strengthen the digital reach and broader impact of LIS research.