论文标题
Botometer 101：计算社会科学家的社会机器人实践
Botometer 101: Social bot practicum for computational social scientists
论文作者
论文摘要
社交机器人已成为在线社交媒体的重要组成部分。尤其是欺骗性的机器人可以操纵在线讨论，从选举到公共卫生，威胁到建设性的信息交换。他们的无处不在使他们成为一个有趣的研究主题，并要求研究人员在使用社交媒体数据进行研究时正确处理它们。因此，对于研究人员而言，重要的是要获得可靠且易于使用的机器人检测工具。本文旨在为Botometer提供一个介绍性教程，这是一种在Twitter上检测到的公共工具，适用于该主题新手并且可能不熟悉编程和机器学习的读者。我们介绍了BOTOMETOR的工作原理，用户可以访问它的不同方式，并将案例研究作为演示。读者可以将案例研究代码用作自己研究的模板。我们还讨论了使用BOTOMETOR的建议练习。
Social bots have become an important component of online social media. Deceptive bots, in particular, can manipulate online discussions of important issues ranging from elections to public health, threatening the constructive exchange of information. Their ubiquity makes them an interesting research subject and requires researchers to properly handle them when conducting studies using social media data. Therefore, it is important for researchers to gain access to bot detection tools that are reliable and easy to use. This paper aims to provide an introductory tutorial of Botometer, a public tool for bot detection on Twitter, for readers who are new to this topic and may not be familiar with programming and machine learning. We introduce how Botometer works, the different ways users can access it, and present a case study as a demonstration. Readers can use the case study code as a template for their own research. We also discuss recommended practice for using Botometer.
