Identification of Twitter Bots Based on an Explainable Machine Learning Framework: The US 2020 Elections Case Study

@article{Shevtsov2021IdentificationOT,
  title={Identification of Twitter Bots Based on an Explainable Machine Learning Framework: The US 2020 Elections Case Study},
  author={Alexander Shevtsov and Christos Tzagkarakis and Despoina Antonakaki and Sotiris Ioannidis},
  journal={ArXiv},
  year={2021},
  volume={abs/2112.04913}
}
Twitter is one of the most popular social networks attracting millions of users, while a considerable proportion of online discourse is captured. It provides a simple usage framework with short messages and an efficient application programming interface (API) enabling the research community to study and analyze several aspects of this social network. However, the Twitter usage simplicity can lead to malicious handling by various bots. The malicious handling phenomenon expands in online… 

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