论文标题
Twitter上的学者的开放数据集
An open dataset of scholars on Twitter
论文作者
论文摘要
研究学者在社交媒体上传播科学知识中所扮演的角色一直是社交媒体指标（Altmetrics）研究中的核心话题。已经实施了不同的方法来识别和表征Twitter等社交媒体平台上的活动学者。过去方法的某些局限性是它们的复杂性，最重要的是，它们依赖于许可的科学计量和高音数据。 OpenAlex或CrossRef事件数据（例如OpenAlex或CrossRef事件数据）的出现提供了机会，仅使用开放数据在社交媒体上识别学者。本文提出了一种新颖而简单的方法，可以将Openalex的作者与CrossRef事件数据中标识的Twitter用户相匹配。描述并用OrcID数据验证了匹配过程。新方法与近500,000个匹配的学者与他们的Twitter帐户相匹配，其精度和中等召回水平。对匹配学者的数据集进行了描述，并公开向科学界公开使用，以增强对Twitter研究学者相互作用的更高级研究。
The role played by research scholars in the dissemination of scientific knowledge on social media has always been a central topic in social media metrics (altmetrics) research. Different approaches have been implemented to identify and characterize active scholars on social media platforms like Twitter. Some limitations of past approaches were their complexity and, most importantly, their reliance on licensed scientometric and altmetric data. The emergence of new open data sources like OpenAlex or Crossref Event Data provides opportunities to identify scholars on social media using only open data. This paper presents a novel and simple approach to match authors from OpenAlex with Twitter users identified in Crossref Event Data. The matching procedure is described and validated with ORCID data. The new approach matches nearly 500,000 matched scholars with their Twitter accounts with a level of high precision and moderate recall. The dataset of matched scholars is described and made openly available to the scientific community to empower more advanced studies of the interactions of research scholars on Twitter.
