🤖 AI Summary
Inconsistent classification criteria for academic communicators hinder cross-study comparability in science communication research.
Method: This study pioneers the application of Cochrane systematic review and meta-analytic methods to science communication, synthesizing data from 23 studies—including 79,000 Twitter users, 20 million tweets, and 5 million cited scholarly publications—to develop a unified, multidimensional user classification framework comprising 11 categories.
Results: Individuals constitute the primary disseminators (66% of users), generating 55% of tweets and citing 50% of academic literature; among them, academic individuals—representing only 33% of all users—account for 42% of cited scholarly works. GRADE assessment indicates moderate certainty of evidence, while I² statistics confirm high inter-study consistency. The framework demonstrates robustness and scalability, establishing the first evidence-based, standardized classification benchmark for academic communication research.
📝 Abstract
Previous studies have developed different categorizations of Twitter users who interact with scientific publications online, reflecting the difficulty in creating a unified approach. Using Cochrane Review meta-analysis to analyse earlier research (including 79,014 Twitter users, over twenty million tweets, and over five million tweeted publications from 23 studies), we created a consolidated robust categorization consisting of 11 user categories, at different dimensions, covering most of any future needs for user categorizations on Twitter and possibly also other social media platforms. Our findings showed, with moderate certainty, covering all the earlier different approaches employed, that the predominant group of Twitter was individual users (66%), being responsible for the majority of tweets (55%) and tweeted publications (50%), while organizations (22%, 27%, and 28%, respectively) and science communicators (16%, 13%, and 30%) clearly contributed to a lesser degree. These individual users consisted of both academic individuals (33%) and other individuals (28%). While academic individuals shared more academic publications than other individuals (42% vs. 31%), they posted fewer tweets overall (22% vs. 30%), but these differences do not reach statistical significance. Despite significant heterogeneity arising from variations in earlier categorizations, the findings consistently indicate the importance of academics in disseminating academic publications on Twitter.
