![]() ![]() 2022, Springer Nature or its licensor holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s) author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. © The Author(s), under exclusive licence to Springer Nature Singapore Pte Ltd. We also discuss recommended practice for using Botometer.īot detection Botometer Social bots Twitter. ![]() ![]() Readers can use the case study code as a template for their own research. We introduce how Botometer works, the different ways users can access it, and present a case study as a demonstration. 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. Each one can help increase social media engagement overnight. Therefore, it is important for researchers to gain access to bot detection tools that are reliable and easy to use. Even if you engage on Twitter religiously, sharing content and engaging with your favorite. Their ubiquity makes them an interesting research subject and requires researchers to properly handle them when conducting studies using social media data. ![]() Deceptive bots, in particular, can manipulate online discussions of important issues ranging from elections to public health, threatening the constructive exchange of information. Social bots have become an important component of online social media. ![]()
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