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 Twitter group was individual users (66%), 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 smaller proportions. The cumulative findings from prior investigations indicated a statistically equal extent of 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 categorization methods, the findings consistently indicate the importance of academics in disseminating academic publications.

翻译：先前研究针对在网络上与学术出版物互动的推特用户提出了多种分类方法，反映出构建统一分类标准的难度。本研究采用科克伦综述荟萃分析方法，对23项早期研究（涵盖79014名推特用户、超过2000万条推文及500万篇被推送的出版物）进行系统分析，构建了包含11个用户类别、覆盖不同维度的稳健分类体系，可满足未来在推特及其他社交媒体平台上对用户分类的大部分需求。研究结果表明（证据等级中等，涵盖此前所有不同分类方法）：个体用户是推特主导群体（占66%），贡献了大部分推文（55%）和被推送出版物（50%），而机构用户（分别占22%、27%和28%）与科学传播者（分别占16%、13%和30%）的贡献比例显著较小。此前研究的累积发现表明，学术型个体（33%）与非学术型个体（28%）在数量上无统计学显著差异。虽然学术型个体分享的学术出版物数量显著多于非学术型个体（42% vs. 31%），但其发布的推文总数较少（22% vs. 30%），且此差异未达到统计学显著水平。尽管分类方法的差异导致了显著异质性，但研究结果一致表明学者在传播学术出版物中具有重要作用。