Sept. 22, 2022, 1:11 a.m. | Lorenzo Mannocci, Stefano Cresci, Anna Monreale, Athina Vakali, Maurizio Tesconi

cs.LG updates on arXiv.org arxiv.org

Online social networks are actively involved in the removal of malicious
social bots due to their role in the spread of low quality information.
However, most of the existing bot detectors are supervised classifiers
incapable of capturing the evolving behavior of sophisticated bots. Here we
propose MulBot, an unsupervised bot detector based on multivariate time series
(MTS). For the first time, we exploit multidimensional temporal features
extracted from user timelines. We manage the multidimensionality with an LSTM
autoencoder, which projects …

arxiv bot detection series time series unsupervised

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