Detecting hate speech on social media and the way it spreads have proved trickier than originally thought. Alt-right politicians seem to be ahead of the technological curve, exploiting existing biases in society and platforms to promote hateful messages. As a result, messages get traction by both good and bad faith actors. In the following research, we examined 36.8 million tweets and 1.5 million unique accounts related to Greek politicians on Twitter, in an effort to map the information dissemination ecosystem. In this chapter, we present a scalable model to predict amplification accounts used by various actors in Greece, alongside a toxicity classifier for short messages. We mainly focused on the political context to scan for toxicity spreaders affiliated to Greek politicians. Our approach investigates behavioral characteristics that differentiate normal accounts with the amplifiers without addressing the binary logic—bot or not. Our preliminary results show that the majority of Greek politicians’ networks of followers are amplifier accounts without necessarily meaning that these are bot accounts. In compatibility with other research findings, we find that the majority of the accounts promoting toxicity are predominantly partisans from the right of the political spectrum.